Miracle-dz/UniFAR-FTUs huggingface dataset:
Predicting prices of agricultural commodities in Thailand using combined approach emphasizing on data pre-processing technique

In this research, a combined approach emphasizing on data pre-processing technique is developed to forecast prices of agricultural commodities in Thailand. The future prices play significant role in decision making to cultivate crops in next year. The proposed model takes ability of MODWT to decompose original time series data into more stable and explicit subseries, and SVR model to formulate complex function of forecasting. The experimental results indicated that the proposed model outperforms traditional forecasting models based on MAE and MAPE criteria. Furthermore, the proposed model reveals that it is able to be a useful forecasting tool for prices of agricultural commodities in Thailand.
These lenses are fundamental tools in a successful refractive surgery practice

T he aim of refractive surgery is to modify the refractive power of the eye in a permanent and stable way. There are two main refractive structures in the eye: the cornea and the natural lens. Changing the shape and thickness of the cornealaser corneal surgery, or exchanging the natural lens for an IOL, as in refractive lens exchange or cataract surgery, allows us to achieve the aim of refractive surgery. However, there is another possibility: introduction of a new refractive surface in the eye without touching the cornea or the natural lens. This is the concept behind phakic IOLs. This article addresses four questions: (1) Why implant phakic IOLs? (2) When should phakic IOLs be implanted? (3) Which phakic IOL should be implanted? and (4) How should a phakic IOL be implanted?
Investigation of wall bounded flows by means of multiple plane stereo PIV

In order to obtain detailed information about the spatial-temporal flow-unsteadiness in the logarithmic region of a fully developed turbulent boundary-layer flow along a flat-plate, the yz-plane (wall-normal / span-wise) was investigated by means of multiple plane stereo PIV, see Kähler and Kompenhans (1999) for technical details. The experiment was performed in the closed circuit wind tunnel at the Laboratoire de Mécanique de Lille with a 20 m long, 2 m wide and 1 m high test-section, Carlier et al (1999). The thickness of the boundary layer developed at the floor of the test-section was 0.37 m at 3 m/s free-stream velocity and the Reynolds number based on the momentum thickness is 7200. The extent of the logarithmic region measures at least 0.06 m as can be estimated from the upper right plot of figure 1 (average over 1250 independent sample fields each containing 13113 vectors) so that outer-flow effects are negligible over a relatively large domain. The distribution of the velocity fluctuations u ′, v′ and w′, the stream-wise vorticity ωx and two components of the Reynolds stress tensor (v′w′ and u′w′) are exactly symmetrical so that a high flow quality and very accurate alignment of the laser and recording system can be assumed in the following. Figure 1. Flow characteristics. Upper row: Mean velocity profile. Center row: Intensities and distribution of the velocity fluctuations. Lower row: Distribution of the Reynolds stresses and stream-wise vorticity. −0.04 −0.02 0 0.02 0.04 −∆(u’v’) [m/s] 0 1e+05 2e+05 3e+05 4e+05 P D F v’w’ u’w’ u’v’ 0 0.01 0.02 0.03 0.04 y [m] 0 0.1 0.2 0.3 0.4 U [m /s ] wrms vrms urms 0 0.02 0.04 0.06 0.08 y [m] 0 1 2 3 U [m /s ] 0.0076 0.0336 Umean −400 −200 0 200 400 ∆ωx [1/s]
Bypassing Memory Leak in Modern C + + Realm

Deallocation of dynamically allocated memory belongs to the responsibility of programmers in the C and C++ programming languages. However, compilers do not support the work of the programmers with error or warning diagnostics. Thus the result of this behaviour can be memory leak. Programs' memory consumption may be unreasonably big and even the operating system can be too slow because of the swapping. We present some di erent scenarios when memory leak is occurred. We show the root cause of the scenarios. This paper presents existing tools for detecting or avoiding memory leak. These tools work in di erent ways. We analyze the smart pointers of C++11 standard, valgrind that is a run-time heap pro ler, Hans Boehm's garbage collector and the Clang static analyzer. We present the pros and cons of the tools. We analyze how di cult to use these tools, how the e ciency is a ected and how these tools can be enhanced for overcome unwanted memory leak. We present our proposals to make the tools more e ective.
The Location Choice of New Immigrants to Canada : The Role of Ethnic Networks

The focus of this paper is on the determinants of the initial location decision of recent immigrants to Canada. Particular attention is given to the role of 'ethnic networks' in this location decision. The ethnic network the concentration of people in the same geographic area who are of similar ethnic background, culture and language can be an important source of financial or personal support, information and guidance, and social mores. Evidence is found that the presence of ethnic networks does have a significant effect on the location decisions of recent immigrants, but the magnitude of the effects depends on personal characteristics of the immigrant such as language and education. JEL Class jflcalion: Jil, J61, J68.
Metabolic Mechanisms of Antitumor Activity of the Glutamine Derivatives

Metabolic mechanisms of realizing the biochemical activity of antitumor low-molecular weight peptide Deglutame (Dg), L-Glutamine (Gln) derivatives, were studied on W-256, SM-1, SM-45 and PC tumor-bearers’ rats. Dg on its enteral and parenteral injection (50 mg/kg) was proved to induce the glycolisis suppression and glucogenesis activation and induces the impoverishment of free amino acids pool in tumor-bearer’s liver. Gln on it’s per oral injection at isomolar Dg dose exerted the single-oriented, but less expressed, influence upon the induce studied. After Dg or Gln injection, Gln concentration decreases while in SM-1 and PC-1 tumor bearers this decrease most evidently is displayed after Dg injection in liver, blood plasma and in the tumor itself, and in tumorous tissue only. Moreover, in blood plasma and liver of W-256 tumor-bearers the total amino acids content, competing with Gln for general systems of transmembranous transport decreases, but it practically does not change in the tumor itself. In liver and blood plasma of SM-1 and PC-1 tumor bearers the total amino acids content, on the contrary, does not change significantly and decreases in tumorous tissue only. After Gln injection the negative correlative relation existing in intact tumor-bearers and confirming the selective Gln absorption by the tumorous tissue between the Gln levels in liver and tumor disappears. According to the data of correlative analysis the “antiglutamine” mechanism of Dg influence is realized only on it’s per oral injection depending on real endogenic (physiological) Gln and amino acids concentrations. Metabolic Mechanisms of Antitumor Activity of the Glutamine Derivatives Department of Biochemistry of Grodno State University, Belarus
A Self-Training Approach for Short Text Clustering

Short text clustering is a challenging problem when adopting traditional bag-of-words or TF-IDF representations, since these lead to sparse vector representations of the short texts. Low-dimensional continuous representations or embeddings can counter that sparseness problem: their high representational power is exploited in deep clustering algorithms. While deep clustering has been studied extensively in computer vision, relatively little work has focused on NLP. The method we propose, learns discriminative features from both an autoencoder and a sentence embedding, then uses assignments from a clustering algorithm as supervision to update weights of the encoder network. Experiments on three short text datasets empirically validate the effectiveness of our method.
Analysis of Data Aggregation Techniques of IOT

-The internet of things is the self configuring network in which sensor nodes can join or leave the network when they want. The security, data aggregation are the two major issues of IOT. In the previous years various techniques are designed to improve data aggregation rate of IOT. The clustering is the technique which can increase data aggregation rate and reduce lifetime of the network. In this paper, various techniques are reviewed to improve lifetime of the network and increase data aggregation rate
IoT Malware : Comprehensive Survey , Analysis Framework and Case Studies

Computer malware in all its forms is nearly as old as the first PCs running commodity OSes, dating back at least 30 years. However, the number and the variety of “computing devices” dramatically increased during the last several years. Therefore, the focus of malware authors and operators slowly but steadily started shifting or expanding towards Internet of Things (IoT) malware. Unfortunately, at present there is no publicly available comprehensive study and methodology that collects, analyzes, measures, and presents the (meta-)data related to IoT malware in a systematic and a holistic manner. In most cases, if not all, the resources on the topic are available as blog posts, sparse technical reports, or Systematization of Knowledge (SoK) papers deeply focused on a particular IoT malware strain (e.g., Mirai). Some other times those resources are already unavailable, or can become unavailable or restricted at any time. Moreover, many of such resources contain errors (e.g., wrong CVEs), omissions (e.g., hashes), limited perspectives (e.g., network behavior only), or otherwise present incomplete or inaccurate analysis. Hence, all these factors leave unattended the main challenges of analyzing, tracking, detecting, and defending against IoT malware in a systematic, effective and efficient way. This work attempts to bridge this gap. We start with mostly manual collection, archival, meta-information extraction and cross-validation of more than 637 unique resources related to IoT malware families. These resources relate to at least 60 1 IoT malware families, and include 260 resources related to 48 unique vulnerabilities used in the disclosed or detected IoT malware attacks. We then use the extracted information to establish as accurately as possible the timeline of events related to each IoT malware family and relevant vulnerabilities, and to outline important insights and statistics. For example, our preliminary analysis shows that the mean and median CVSS scores of all analyzed vulnerabilities employed by the IoT malware families are quite modest yet: 6.9 and 7.1 for CVSSv2, and 7.5 and 7.5 for CVSSv3 respectively. Moreover, the public knowledge to prevent or defend against those vulnerabilities could have been used, on average, at least 90 days before the first malware samples were submitted for analysis. Finally, to help validate our work as well as to motivate its continuous growth and improvement by the research community, we open-source our datasets and our IoT malware analysis framework. ‡ Affiliated also with the Firmware.RE Project (andrei@firmware.re). 1 IoT malware families that we are aware of at the time of this writing, and that are publicly disclosed, analyzed or otherwise reported.
Decembar 2007 233 The Impact of Data Mining on System Analysis Process

With the advent of the computer age, people have begun using computers to automate the data gathering process and store the information in databases. Computers are so well suited to this task that huge databases with terabytes of information have been generated. It is well beyond the scope of the human mind to sort through all of this data and find any useful patterns for predicting future events. The mining has been invented as one technique of the machine learning field to deal with this new problem by using computers to automate the process of searching data in huge databases for useful patterns, which is can used to build a new system. In this paper we need to show how data mining techniques can help the systems analysts people for studying and extract facts for building new systems.
PEMBELAJARAN BERBASIS MASALAH UNTUK MENINGKATKAN LITERASI SAINS PADA MATERI HUBUNGAN MAKANAN DENGAN KESEHATAN

Problem Based Learning to Improve Science Literacy on Food Relation with Health. Science literacy is ability to review a problem or phenomenon on the point of science view. Science literacy can be enhanced trough the problem-solving process in science learning. Teacher roles as the information center, transforms into facilitator, motivator and creator to help construct student knowledge. Problem based learning process allows students to be actively involved because given the opportunity to solve a problem related to an event. Problem-based learning affects both the science literacy students of class V on the relationship of food to health. This is evidenced by the research using pre-experiment method with pretest-postest one group design which shows that problem-based learning can significantly increase students literacy ability in high, medium and low group. Based on the results of the study problem-based learning can be used as a solution to improve literacy skills of elementary school students.
The Almighty Quasar — Destroyer of Worlds

In the study of habitability of terrestrial exoplanets, both life-supporting conditions and the prevalence of transient life-threatening events need to be considered. One type of hazardous effect that has so far not received much attention is the thermal effect of a nearby active galactic nucleus (AGN), or in this particular case, the class of the AGN known as a quasar. In this work we investigate the thermal effect from a quasar by calculating the number of habitable terrestrial planets (HTP) in an elliptical or bulge-dominated galaxy, that goes extinct when exposed to the quasar radiation in a limited wavelength range. This is done by approximations and modelling along with pre-existing formulas and data from earlier publications. As a result, the influence by a quasar during the time span of quasar activity will have a less significant impact on the habitability in solar-type stellar systems than expected. Assuming tQSO “ 10 yrs of quasar activity, results in the number of affected HTP, « 1ˆ10, 9ˆ10 and 4ˆ10 for isotropic spherical radiation and « 1ˆ10, 8ˆ10 and 3ˆ10 for a double-conical radiation. In terms of stellar mass fraction, « 1.3%, 1.0%, 0.4% for isotropic radiation and « 12.8%, 9.5%, 3.8% for conical, is affected. The results of this work are hoped to provide a rough estimation of the thermal impacts of a quasar on the habitability as well as to point out the most important parameters when considering this model.
Volatility as Investment-Crash Protection with Calendar Spreads of Variance Swaps

Nowadays, volatility is not only a risk measure but can be also considered an individual asset class. Variance swaps, one of the main investment vehicles, can obtain pure exposure on realized volatility. In normal market phases, implied volatility is often higher than the realized volatility will turn out to be. In this paper, we show a volatility investment strategy which can benefit from both negative risk premium and correlation of variance swaps to the underlying stock index. The empirical evidence demonstrate a significant diversification effect during the financial crisis by adding this strategy to the equity portfolio. The back testing analysis includes the last ten years of history of the S&P500 and the EUROSTOXX50. ∗We thank Nils Detering for his contribution a previous German version of this paper, Julia Weinhardt for proof-reading the English version and Lupus alpha for supporting the research work.
Sea Nomads and Rainforest Hunter-Gatherers: Foraging Adaptations in the Indo-Malaysian Archipelago

This chapter discusses the non-agricultural aspects of Austronesian history and ethnography, taking the basic view that the early Austronesian colonizations might have involved a range of both food producing and foraging economies and that sharp dichotomies between the two kinds of economy are unlikely to have existed. Modern Austronesian hunter-gatherers such as the Agta and Penan cannot be seen as “fossilized” foragers from the Pleistocene, but, like the Semang, as parties to a process of symbiosis with agriculturalists which has continued for several millennia. The idea of “devolution” from a prior dependence on agriculture amongst the Penan is critically assessed and rejected. Also discussed are the historical roles of the Sea Nomads — Moken, Orang Laut and Sama-Bajau.
ffi cient MapReduce-Based Parallel Processing Framework for User-Based Collaborative Filtering

User-based collaborative filtering is one of the most-used methods for the recommender systems. However, it takes time to perform the method because it requires a full scan of the entire data to find the neighboring users of each active user, who have similar rating patterns. It also requires time-consuming computations because of the complexity of the algorithms. Furthermore, the amount of rating data in the recommender systems grows rapidly, as the number of users, items, and their rating activities tend to increase. Thus, a big data framework with parallel processing, such as Hadoop, is needed for the recommender systems. There are already many research studies on the MapReduce-based parallel processing method for collaborative filtering. However, most of the research studies have not considered the sequential-access restriction for executing MapReduce jobs and the minimization of the required full scan on the entire data on the Hadoop Distributed File System (HDFS), because HDFS sequentially access data on the disk. In this paper, we introduce an efficient MapReduce-based parallel processing framework for collaborative filtering method that requires only a one-time parallelized full scan, while adhering to the sequential access patterns on Hadoop data nodes. Our proposed framework contains a novel MapReduce framework, including a partial computation framework for calculating the predictions and finding the recommended items for an active user with such a one-way parallelized scan. Lastly, we have used the MovieLens dataset to show the validity of our proposed method, mainly in terms of the efficiency of the parallelized method.
From an irrigation system to an ecological asset: adding environmental flows establishes recovery of a threatened fish species

Worldwide, riverine fish are the target of environmental water because populations have declined in lotic river habitats following river regulation. Murray cod is an endangered Australian riverine fish with remaining populations associated with lotic river reaches with instream habitat, including some creeks operated as part of irrigation systems. Our objectives were to develop a life history model, apply the building block method of environmental flows to enhance the abundance of juvenile Murray cod and promote population recovery. From 2008 to 2018 we evaluated changes to Murray cod juvenile abundance before and after implementation of a perennial environmental flow regime that began in 2013. During the first year of the environmental flow, larvae were collected as evidence of spawning. Murray cod abundance can be enhanced with environmental flows that target: (1) an annual spring spawning or recruitment flow with no rapid water level drops; (2) maximising hydrodynamic complexity (i.e. flowing habitats that are longitudinally continuous and hydrodynamically complex); and (3) an annual base winter connection flow. Recognition that incorporating hydraulics (water level and velocity) at fine and coarse time scales, over spatial scales that reflect life histories, provides broader opportunities to expand the scope of environmental flows to help restore imperilled fish species in regulated ecosystems.
Feature Landowners , Bioenergy , and Extension Strategies

Given increased energy demand from alternative sources, wood-based bioenergy is receiving significant policy and research attention in the United States. Many private forest landowners, who are the likely feedstock suppliers for wood-based bioenergy, however, are not completely aware of its opportunities and potential positive and negative impacts. This article, therefore, reviews the existing work on status of biomass availability and landowner motivations for supplying biomass for wood-based bioenergy industry. Some educational needs of landowners and the potential role of Extension professionals are highlighted.
Snapshot Isolation for Neo 4 j 1

NoSQL data stores are becoming more and more popular. Graph databases are one of this kind of data stores. Neo4j is a very popular graph database. In Neo4j all operations that access a graph must be performed in a transaction. Transactions in Neo4j use read-committed isolation level. Higher isolation levels are not available. In this paper we present an overview of the implementation of snapshot isolation (SI) for Neo4j. SI provides stronger guarantees that read-committed and provides more concurrency than serializability.
NoSQL Paradigm and Performance Evaluation

Digital world is advancing by leaps and bounds thus becoming complex in terms of volume, variety and velocity. This is called the Big Data i.e. a large chunk of combined structured, semi structured & unstructured data that cannot be steered by relational databases. A new trend referred to as web2.0 is now coming into picture due to massive growth in the Internet market and surfacing of the new web technologies[1]. In order to handle these challenges the concept of NoSQL technology has been evolved as an alternative to the traditional relational database systems. This paper targets at comprehending various aspects of NoSQL, its classifications, their characteristics and evaluation of each. It aims at providing answers of the problems of handling Big Data and their analysis. Keywords—NoSQL, ACID, BASE, CAP,
Visual and Cognitive Demands of Using In-Vehicle Infotainment Systems

The features of vehicle-based infotainment technology have greatly expanded in recent years, opening up a new array of tasks accessible to motorists while driving. Many of these new functions are unrelated to driving. Examples include voice commands to send a text message, check social media or surf the web. Furthermore, many tasks distract motorists from driving by diverting their eyes and attention from the road and hands from the steering wheel. Yet, surprisingly, little is known about how these interactions may affect a driver’s performance when the demands are high.
Relationship between human capital and economic growth : The case of Austria

Impact of education, more precisely impact of skills and knowledge (human capital) to increase individual productivity and wealth of a nation, was already emphasized by classical economists. However, their opinions and findings were not included in detailed analyses and systematically processed. Comprehensive concepts of theory of human capital were introduced in the early Sixties of 20 century. In the last twenty years, the influence of human capital was confirmed by many economic studies, more precisely influence of education on economic growth and productivity. On the contrary, some experts criticize this unambiguous and inconclusive relation and some of them even disprove this hypothesis, publishing their studies. This paper considers the relationship of human capital and economic growth in Austria. The importance of human capital in the economic growth of this country is being proven by using two types of econometric analyses. One of them is cointegration test, which is followed by error correction model. In terms of concept simplification, the value of human capital is expressed by the level of education. We found out that positive long-run relationship exists between human capital and economic growth, i.e. national competitiveness.