Miracle-dz/UniFAR-FTUs huggingface dataset:
Türkiye İnşaat Sektörünün Global Karbon Ayak izi Analizi

Turkiye insaat sektorunun ekonomik, cevresel, ve sosyal etkilerinin analizi son yillarda onemini giderek artirmistir. Ozellikle artan insaat, ulasim, uretim ve enerji yatirimlari Turkiye ve dunya ekonomisine dogrudan ve dolayli etkiler yapmaktadir. Bu makalede, Turkiye icin onemli bir arastirma boslugunu doldurmak amaciyla Turkiye’deki insaat sektorunun uluslararasi tedarik zincirlerini de kapsayacak bir bicimde ilk, web tabanli ve kuresel karbon ayakizi analizi yapilmistir. Avrupa Komisyonu 7. Cerceve Arastirma Programinca desteklenen Dunya Girdi-Cikti Veritabani’nin ‘World Input-Output Database’ Turkiye insaat sektoru icin ilk kez kullanilacagi bu calismada, Turkiye insaat sektorunun 2000 ile 2009 yillari arasindaki karbon ayakizi etkilerini ulusal ve kuresel capta analiz edilmistir. Bu sekilde Turkiye insaat sektorlerinin bolgesel ve kuresel duzlemde cevresel etkileri hesaplanarak kapsamli surdurulebilirlik analizleri yapilmistir. Onerilen modelin benzer versiyonlari Amerika Birlesik Devletleri, Avrupa Birligi, Avusturalya, Ingiltere ve Japonya gibi birinci dunya ulkelerinde stratejik karar vermede kullanildigi halde, Turkiye icin benzer kapsamli bir model henuz mevcut degildir. Bu motivasyonla, ‘Kuresel Karbon Ayakizi Muhasebe Modeli’ (Global Carbon Footprint Accounting Tool) gelistirilmis ve insaat sektoru icin kapsamli bir analiz yapilmistir. Harvard’li unlu ekonomist Wassily Leontief’in ekonomi alaninda Nobel Odulu kazandigi girdi-cikti analizinin kuresel modele donusturulerek kullanilacagi bu calisma, zaman serisi analizi, kapsam bazli karbon ayak izi modellemesi, uretim-tuketim odakli, ve kuresel etki dagilimi analizi gibi yenilikci yontemlerle kullanicilara tedarik zinciri odakli analizler yapma imkani saglamaktadir. Analiz sonuclarina insaat sektorundeki buyumeden kaynakli salinimlar, 2000-2009 yillari arasi verimlilik artisindan dolayi azalan karbon salinimlarina gore daha fazla oldugu icin, sektorun bu yillar arasi toplam salinimi artmistir. Insaat sektorunun Kapsam 2 ve 3 karbon salinimlari (dolayli salinimlar) sektorun toplam emisyonlarinin ortalama %80’nine karsilik gelmektedir ve sektorun emisyonlarini dusurmek icin tedarik zinciri ile beraber degerlendirilmesi gerekmektedir. Arastirma sonucunda gelistirilen kuresel modelin basta bakanliklar olmak uzere, arastirma enstituleri ve universitelerdeki karar verme sureclerinde yaygin bir bicimde kullanilabilmesi icin web-tabanli bir sekilde internet ortaminda da sunulmustur.
Utilization of Constructivist Instructional Method in Teaching Physics in Secondary Schools: Interaction Effects of Method and Location

In this study, the researcher investigated the interaction effects of method and location on academic achievement of secondary school physics students using constructivist teaching method. Pretest-posttest non-equivalent control group design was adopted. The study was conducted in Enugu North and East Local government Areas of Enugu state. The population of the study was 5,104 senior secondary one (SS1) Physics students. The sample size was 118 (60 males and 58 females). Stratified random sampling was used to draw two co-educational schools, one from Urban Schools and the other from rural schools. In each of the two schools sampled, two intact classes were randomly sampled from SS1 Physics students. One out of the two classes sampled was assigned to constructivist teaching method while control group was assigned to lecture method. Three research questions and three null hypotheses guided the study. The duration of the experiment lasted for four weeks. Data generated were analyzed using mean with standard deviation. Analysis of Covariance (ANCOVA) was used in testing the hypothesis at Plt 0.05. The results of the study showed that the studentsrsquo achievement in Physics was better when they were taught basic concept of electricity using constructivist teaching method than when they were taught using lecture method. The results also showed that location had a significant influence on academic achievement of Physics students in favour of urban schools. From the result of the study, significant (plt0.05) interaction effect due to method and location on studentsrsquo achievement in Physics was observed. Based on the findings some recommendations were made.
Enhancing the Control of Upper Limb Myoelectric Prostheses Using Radio Frequency Identification

Multi-articulating prosthetic devices are yet to meet a control method that can match their potential. Outdated methods, like using electromyography (EMG) triggers to switch among different grips, have led people to frustration, fatigue and loss of faith. User experiences and statistics on myoelectric use and abandonment have indicated that an easier and more reliable solution is needed. It is my belief that radio frequency identification (RFID) holds the key to mitigating many of the limitations present in current methods. By allowing users to access the grips they need by approaching different RFID tags in their environment or on person, this alternative reduces the risk of uncertainty and frustration present in current methods. Furthermore, by creating a hybrid approach that allows both RFID and EMG triggers as control switches, the user can personalize the solution and decide which approach is more favorable based on different situations. The introductory chapter of this thesis provides an overview of EMG-based control for myoelectric devices. It includes both literature and a user needs analysis that highlight the strengths and weaknesses of the approach. Chapter 2 discusses RFIDii
Analysis of the Operational Constraints of the Rice Value Chain in Ayeyarwaddy Region, Myanmar

The rice industry is the most important agriculture subsector in Myanmar. However, far lower profits are gained from producing rice in Myanmar compared with those gained in other rice-producing ASEAN countries. This paper analyzes the operational constraints experienced by the different actors in the rice value chain in Myanmar. Both primary and secondary data on the rice value chain in Ayeyarwaddy Region, the main rice-growing area in Myanmar, were collected. The actors in the region suffer from constraints in material input, production, financial, distributional, and institutional. This study examines the actors’ profitability, together with their sociodemographic and operational characteristics, to provide proper policy guidelines to address constraints. The analysis revealed that the value chain in the study area is structurally inefficient, characterized by a large number of actors who face numerous constraints. Diverse policy recommendations are then put forward to improve the rice value chain in the Ayeyarwaddy Region. Stakeholders need to implement projects that would increase the quantity and quality of rice produced, ranging from input quality control to more efficient extension services. Credit and sufficient working capital should also be provided to make infrastructure investments possible at each stage of the value chain in order to improve production and profitability.
Electronic and computation technologies in data collection and integration in precision agriculture.

The population growth and consequent demand for food, water scarcity, rigid quality standards and legislation, higher concern about environmental impact, among other factors, have powered a new agricultural paradigm grounded in sustainability and higher productivity of crops. In this sense, precision agriculture is an alternative to traditional cultivation techniques, where the use of information technologies in decision support systems reduces the risks associated to cultivation conditions, enabling a more efficient management of natural resources, improving the productivity and minimizing the operation costs. This work aims the revision of some electronic and computers technologies used in precision agriculture systems, regarding remote sensing techniques, sensors networks, visual inspection and data
Vision Science Photons To Phenomenology

Thank you for reading vision science photons to phenomenology. Maybe you have knowledge that, people have search numerous times for their chosen readings like this vision science photons to phenomenology, but end up in malicious downloads. Rather than enjoying a good book with a cup of coffee in the afternoon, instead they cope with some harmful bugs inside their laptop. vision science photons to phenomenology is available in our digital library an online access to it is set as public so you can download it instantly. Our books collection hosts in multiple locations, allowing you to get the most less latency time to download any of our books like this one. Kindly say, the vision science photons to phenomenology is universally compatible with any devices to read.
La evolución de un school leader: A case study

ABSTRACT As American children grow more culturally and linguistically diverse, many teachers, school leaders, researchers, and policy makers are implementing bilingual instruction as a means to assist these students. There are a variety of bilingual teaching methods, just as there are a variety of English language learning students. From English as a Second Language to Sheltered English Instruction, and from transitional bilingual teaching to two-way immersion, there are a number of ways to teach students in more than one language. This case study examines the experiences of one principal as he implemented a two-way immersion (TWI) program for his urban, parochial school located in a city in the Southwest United States, referred to in this study as “River City. ” The school’s context is considered as well: a parochial elementary school—not far from the city center in a highly diverse metropolis, in a highly diverse state. This study examined the principal’s evolving leadership strategy in implementing the bilingual curriculum as a member of a national network of parochial schools transitioning to such teaching. In so doing, the study is situated within a broader discussion of school leadership that occurs in changing school environments, as well as the complexities leaders face when responding to the needs of culturally and linguistically diverse (CLD) students and their families. The study asks: What is the social and historical local context for the school in which TWI implementation takes place? And in what ways does a school principal learn to respond effectively to the school’s context?
Using morphology to improve Example-Based Machine Translation: The case of Arabic-to-English translation

We describe how morphological information was used in an Example-Based Arabic-to-English Machine Translation system to produce significant improvement in translation quality on both small and large corpora. We experimented with different methods of generalizing morphology to obtain more candidate source-side matches, while retaining information about the specific input to be translated. This information was then used with adaptation rules and a language model to generate context-appropriate target-side fragments, select and combine them. We outline essential differences between Statistical MT (SMT) and Example-based MT (EBMT), compare ourselves to other EBMT systems used with morphologically complex languages, and justify our choice of EBMT over SMT.
The training of convolution neural network for advanced driver assistant system

In this paper, the learning technique for CNN processor on vehicle is proposed. In the case of conventional CNN processors, weighted values learned through training are stored for use, but when there is distortion in the image due to the weather conditions, the accuracy is decreased. Therefore, the method of enhancing the input image for classification is general, but it has the weakness of increasing the processor size. To solve this problem, the CNN performance was improved in this paper through the learning method of the distorted image. As a result, the proposed method showed improvement of approximately 38% better accuracy than the conventional method.
Alcohol Consumption- Influence on Global Population

Liquor keeps on being a standout amongst the most often mishandled medications on the planet. While low levels of liquor utilization may have medical advantages, ceaseless ill-use of liquor harmfully affects most body frameworks and adds to or intensifies more than sixty malady conditions. [1] Beverages containing ethanol are normally known as hard beverages. [2] Ethanol is an old recreational and social drink effectively acquired by maturation of sugars and devoured all through the world. The most elevated amount of utilization is seen in created countries. [3] In the course of recent decades the utilization of illicit medications and abuse of helpful medications has spread at a remarkable rate and influences all aspects of the globe. [4] Wine is a standout amongst the most widely recognized hard drinks expended everywhere throughout the world. [5] Moderate liquor utilization is connected with enhanced health. [6] Liquor utilization is connected with the main sources of death among youth. [7] An anomalous practical association in the cerebrum of a person with addictive issue brings about an upgraded notability of medication related signals and debilitated subjective control. [8] Liquor is a known human teratogen that creates physical, mental, behavioral and psychological abnormalities. [9] Stroke is one of the significant reasons for death in the created world and a main ten benefactor to the worldwide weight of sickness. Russia has one of the world's most noteworthy stroke rate and death rates. A few studies have stressed the part of hitting the bottle hard as vital determinant of high stroke death rate in Russia. [10] DESCRIPTION
Bankruptcy Prediction through Artificial Intelligence

INTRODUCTION Bankruptcy prediction or corporate failure is considered a classic issue in both, academic and business communities. Bankruptcy risk is one of the most important factors (if not the most important one) to be considered when credit requests are screened or even existing debtors are evaluated. On the other hand, all potential stakeholders (shareholders, suppliers, customers, employees, creditors, auditors, etc.) have potential interest to identify if a company is on a trajectory that is tending towards failure. Commercial banks, public accounting firms and other institutional entities (e.g., bond rating agencies) appear to be the primary beneficiaries of accurate bankruptcy prediction, since they can use research results to minimize exposure to potential client failures. In addition to avoiding potentially troubled obligors, the research can also benefit in other ways. It can help in accurately assessing the credit risk of bank loan portfolios. Credit risk has been the subject of much research activity, since the regulators are acknowledging the need and are urging the banks to assess the credit risk in their portfolios. Measuring the credit risk accurately also allows banks to engineer future lending transactions, so as to achieve targeted return/risk characteristics. The other benefit of the prediction of bankruptcies is for accounting firms. If an accounting firm audits a potentially troubled firm, and misses giving a warning signal then it faces costly lawsuits (Atiya, 2001). A series of techniques have been applied in literature. Econometric / statistical methods have first appeared in literature: In late 1960's (multiple) discriminant analysis (DA) was the dominant method; during the 1980's logistic analysis. In the 1990's artificial intelligence starts appearing in financial literature with neural networks (Odom & Sharda 1990) serving as an alternative to statistical methods demonstrating promising results. The goal of this chapter is therefore twofold: First, it intends to give an overview of the artificial intelligence techniques successfully applied to the problem, ranging from the first neural network applications to recent applications of biologically inspired algorithms, such as genetic algorithms. Then, two kernel based methods, namely the Radial Basis Function Neural Networks and the Support Vector Machines are applied to the bankruptcy problem.
Stimuli design for SSVEP-based brain computer-interface

The paper presents a process of stimuli design for SSVEP-based brain computer-interface. A brain computerinterface can be used in direct communication between a brain and a computer, without using muscles. This device is useful for paralyzed people to communicate with the surrounding environment. Design process should provide high accuracy recognition of presented stimuli and high user comfort. It is widely known how to make stimuli for BCI which are using high-grade EEG. Over recent years cheaper EEGs are becoming more and more popular, for example OpenBCI, which uses ADS1299 amplifier. In this article we review past works of other authors and compare it with our results, obtained using EEG mentioned before. We try to confirm that it is possible to use successfully OpenBCI in BCI projects.
Extracting the Sentiment Score of Customer Review from Unstructured Big Data Using Map Reduce Algorithm

Big Data is a term used to identify the datasets that due to their large size, is very difficult to manage with traditional techniques. This data may be in the order of magnitude of petabytes. It can be found easily on web, especially on social media in the form of customer blogs, reviews and comments. Generally it is unstructured data or semi-structured data. One can use this big data to generate values by calculating sentiment score. Map Reduce is one of the most popular algorithm in Hadoop environment to perform such task. The objective of present research is to automate the process of extracting sentiments expressed about specific features of a product. For this purpose three datasets generated by Amazon for different types of electronics product reviews has been used. The data sets used consists of reviews of the products Nikon Coolpix 4300 Camera, Nokia 6601 mobile and the Canon G3camera. Map Reduce algorithm on Hadoop environment that is considered faster, reliable and fault-tolerant for processing big amounts of data in-parallel on large clusters, has been used to extract sentiment score.
Parallel Multistart Nonlinear Optimization with PROC OPTMODEL

Nonlinear optimization has many compelling applications, including finance, manufacturing, pricing, health care, telecommunications, engineering, and statistics. Often a nonlinear optimization problem has many locally optimal solutions, making it much more difficult to identify a globally optimal solution. That’s why the multistart feature in PROC OPTMODEL selects a number of initial points and starts optimization from each one, significantly improving your chances of finding a global optimum. In SAS/OR ® 12.1, the multistart feature adds parallel execution. This paper explores the multistart feature and its parallel optimization feature, illustrating with examples drawn from research and industry.
Predicting Test Case Verdicts Using Textual Analysis of Committed Code Churns

Background: Continuous Integration (CI) is an agile software development practice that involves producing several clean builds of the software per day. The creation of these builds involve running excessive executions of automated tests, which is hampered by high hardware cost and reduced development velocity. Goal: The goal of our research is to develop a method that reduces the number of executed test cases at each CI cycle. Method: We adopt a design research approach with an infrastructure provider company to develop a method that exploits Machine Learning (ML) to predict test case verdicts for committed source code. We train ﬁve diﬀerent ML models on two data sets and evaluate their performance using two simple retrieval measures: precision and recall Results: While the results from training the ML models on the ﬁrst data-set of test executions revealed low performance, the curated dataset for training showed an improvement on performance with respect to precision and recall. Conclusion: Our results indicate that the method is applicable when training the ML model on churns of small sizes. verdicts by training a machine learning model on historical test executions and code churns. We have evaluated the method using two data sets, one containing a variation of large and small churns, and a second containing only small churns. The results from training the models on small churns revealed a precision rate of 73% and a recall of 43.6%, suggesting that the application of the
CROSS LAYERED HYBRID TRANSPORT LAYER PROTOCOL APPROACH TO ENHANCE NETWORK UTILISATION FOR VIDEO TRAFFIC

Video data transfer is the major traffic in today’s Internet. With the emerging need for anytime anywhere communication, applications transmitting video is gaining momentum. Real Time Protocol is the primary standard for transfer of video data, as; it requires timely delivery and can tolerate loss of packets. Streaming is the method used for delivering video content from the source server to the user. But this has many drawbacks: a) It sends only the amount of data equivalent to the streaming encoded rate to the client irrespective of the available bandwidth in the path. Hence the links are underutilized; b) It utilizes the link for the entire period of transfer and hence the link is not available to service other new clients. Thus as the number of clients increases, the network performance decreases. In this work, the advantages and disadvantages of the combination of different protocols in the application layer and transport layer are analyzed. The significant characteristics of each of these protocols are utilized and a combination of protocols for improving the network performance is arrived at, while retaining the QoS of video transmission.
An Automatic Building-layout Algorithm Based on Inner Available Region

In order to implement the automation in the building-layout,an efficient method for automatic layout of buildings in the planned area has been proposed,which takes sunshine time and the fire space between buildings into account. It could arrange buildings on the style of determinant arrangement and peripheral arrangement,referring to the algorithms for the orthogonal rectangular packing problem and the algorithms for the no-fit polygon. Proposed an algorithm of calculating the inner available region for one polygon which stands for the building-covered region with respect to another polygon which stands for the planned area. Then,the determinant arrangement buildings were arranged by the bricklaying algorithm in the inner available region and the peripheral arrangement buildings were arranged along the boundary of the inner available region. At the end,some examples were presented to verify the method.