Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of Vedic Multiplier with Conventional Array and Wallace Tree Multiplier

In the design of most high performance systems such as FIR filters, image processing, microprocessors multipliers are the integral components and multiplication is the important fundamental function in arithmetic operations. A CPU (central processing unit) devotes a considerable amount of processing time for performing arithmetic operations. High speed processors depends greatly on the multipliers, Multiplication requires substantially more hardware resources and processing time than addition and subtraction. Since multiplication dominates the execution time of most DSP algorithms, there is a need of high speed multiplier. Currently the speed of the multipliers is limited by the speed of the adders used for partial product addition. In this paper, we proposed a high speed 8-bit multiplier using a Vedic Mathematics (Urdhva Tiryagbhyam sutra) [1]for generating the partial products. And comparison of this 8-bit Vedic multiplier using RCA with conventional array multiplier, Wallace tree multiplier and 8-bit Vedic multiplier using CLA. Simulation and synthesise of the design is carry out using Xilinx ISE 14.7.
NOTES AND COMMENTS GIFT EXCHANGE IN THE FIELD BY ARMIN FALK

This study reports evidence from a field experiment that was conducted to investigate the relevance of gift exchange in a natural setting. In collaboration with a charitable organization, we sent roughly 10,000 solicitation letters to potential donors. Onethird of the letters contained no gift, one-third contained a small gift, and one-third contained a large gift. Treatment assignment was random. The results confirm the economic importance of gift exchange. Compared to the no gift condition, the relative frequency of donations increased by 17 percent if a small gift was included and by 75 percent for a large gift. The study extends the current body of research on gift exchange, which is almost exclusively confined to laboratory studies.
Unsupervised Symmetric PolygonMeshMapping The Dualism of Mesh Representation and Its Implementation for Many Layered Self-OrganizingMap Architectures

With this paper we present a fully automated semantic shape similarity detection based on N-rings with further potential for shape synthesis in a topological correct feature space. Therefore a way of symmetric encoding of geometry, optimized for the use as feature-vector in self-organizing maps, is introduced. Furthermore we present a modified kernel for the detection of the best matching unit in self-organizing maps especially designed for a data topology differing from the default predecessor/successor structure. Finally we provide the results of a conducted experiment clustering building blocks of an area in Zürich, Switzerland.
Control System for a Dual-stage High-precision Electromechanical Motion Platform

This thesis describes the development of a control system for a high precision dual-stage platform, which is a part of an industrial assembly robot of optical components. The task consists of a driver electronics design for a voice coil motor and its subsequent use as a part of control system for the dual stage and possible future replacement of the curret industrial driver. A consequential part of the thesis resides in designing the control strategy for the task of soft landing as an improvement over the conservative industrial approach. This is achieved by developing a hybrid model of the dual stage system used in a hybrid model predictive controller in simulation, based on which a consequent suboptimal model predictive control strategy with heuristics is designed and successfully applied on the dual-stage system. The control program is realized on the dSpace MicroLabBox platform.
Modeling and identification of a chemical storage tank

The objectives of this diploma thesis are to learn about thermodynamical processes in a chemical industry, based on the knowledge learned, to create and to identify a model of a thermodynamical process in a real chemical tank. To create a model the chemical tank itself is described with regards to its shape, sensor placement and physical properties. Model will be identified using real data. Data for identification will be analysed to avoid problems during identification. Methods used will be both linear and nonlinear according to own choice, validated on a real data samples. Results of all approaches taken to identify the model will be compared to decide which method prvided the best results. Current control approach is described and possible improvements are suggested.
- 1-Argentina , Kirchnerismo , and Neodesarrollismo : Argentine political economy under the administration of Nestor Kirchner 2003-2007

The national Peronist social contract in Argentina has a long history rooted in syndicalism and Latin American populism. However, Menemismo in the 1990s, El Argentinazo in December 2001, and Kirchnerismo post crisis have all served to change the fundamental framework of the Argentine economy, and how that economy intersects with global capital. This paper is an attempt to identify the nature of Kirchner’s administration. Analysis is therefore focused on both domestic policy and political economy, as well as on more international intersections due to a context of understanding that the state plays a key role in mediating between the internal and external (read: national and international) forces placed upon it in a development context. Therefore, through analysis of factors such as domestic economic and industrial policy, as well as external relations with organisations such as the IMF and the Paris Club of Debtors, this paper seeks to facilitate a deeper understanding of the developmental nature and impact of the Kirchner administration of 2003-2007.
New Strategies for Fungal Infections after Hematopoietic Cell Transplantation : Prevention or Preemption ?

allogeneic hematopoietic cell transplant (HCT) recipients. New drugs such as the echinocandins (caspofungin, micafungin, and anidulafungin) and the extended-spectrum azoles (itraconazole, voriconazole, and posaconazole) offer more effective and safer options today. Although these potent antifungal agents make treatment prospects better, there still is considerable risk for death from Candida, Aspergillus, and other mold infections. Accordingly, considerable interest resides in figuring out what is the most effective strategy in using antifungal agents to optimize patient outcomes. Identification of risk factors allows greater focus on patients and transplantation complications that warrant a higher degree of vigilance for fungal infections. New imaging techniques and rapid diagnostic assays allow earlier institution of therapy. The success of fluconazole in dramatically reducing Candida infections has led to hope that similar approaches to prevent Aspergillus and other mold infections may also be successful. In this issue of BMTR, the subject of how best to mitigate the threat of invasive fungal infections is addressed in the proceedings of a satellite symposium presented at the 2007 BMT Tandem Meetings in Keystone, Colorado. In the first presentation, Dr. Richard Champlin presents an overview of the problem and describes historical treatment approaches. In the second presentation, Dr. John Wingard discusses the rationale for prophylaxis and reviews the results of the various clinical trials that have tested this approach with different antifungal agents. In the third presentation, Dr. Dimitrios Kontoyiannis discusses the basis for and the data to support empiric and preemptive therapy approaches. Enormous strides have been made in refining treatment options for invasive fungal infections. These are gradually chipping away at the threat. Yet, much work remains. Testing of which strategy optimizes patient outcomes has been started but greater understanding of what works best for whom is needed. New Strategies for Fungal Infections after Hematopoietic Cell Transplantation: Prevention or Preemption?
A Rank Aggregation Algorithm for Efficiently Searching Top-k Semantic Similar Sentences

Measuring semantic similarity between sentences is an important issue in many applications, such as, text mining, Web page retrieval, dialogue systems, and so forth. Although it has been explored for several years ago, most of these studies focus on how to improve the effectiveness issue but not efficiency. In this paper, we address the efficiency issue, i.e., for a given sentence collection, how to efficiently discover the top-k most semantic similar sentences to the query. It is a very important issue for real applications while existing state-of-the-art strategies cannot satisfy the performance requirement of the users. We introduce a general framework to tackle the issue, in which several efficient strategies are proposed. Extensive experimental evaluations demonstrate that our approach outperforms the state-of-the-art methods.
Institutionen För Systemteknik Department of Electrical Engineering Examensarbete Laser Triangulation Using Spacetime Analysis Laser Triangulation Using Spacetime Analysis

In this thesis spacetime analysis is applied to laser triangulation in an attempt to eliminate certain artifacts caused mainly by reflectance variations of the surface being measured. It is shown that spacetime analysis do eliminate these artifacts almost completely, it is also shown that the shape of the laser beam used no longer is critical thanks to the spacetime analysis, and that in some cases the laser probably even could be exchanged for a non-coherent light source. Furthermore experiments of running the derived algorithm on a GPU (Graphics Processing Unit) are conducted with very promising results. The thesis starts by deriving the theory needed for doing spacetime analysis in a laser triangulation setup taking perspective distortions into account, then several experiments evaluating the method is conducted.
Estimating method on choosing the item in E-Commerce

EC サイトにおいての重要な課題は,自顧客のニーズの把握 しマーケティング戦略に活用することである. これまで POS データを利用し, ブランドのロイヤリティ推定や価格の受領 範囲等,顧客の商品選択行動をテーマとした様々な研究が行わ れている. また,顧客を理解するために,購買結果だけでなく, 購買する際候補とした商品 (考慮集合)と実際に購買したものの 関係を捉え,商品選択行動を明らかにするというアプローチの 必要性も唱えられてきた. こうした考慮集合を把握は,実店舗 で行うことは難しかったが,EC サイトでは,個人の探索,商 品閲覧,購買までを一連の流れとして捕らえることができる. 特にファッション,服飾品などの分野では,購買サイクルが不 定期であること,同一商品を購買が見られないことなどから商 品選択行動の把握が困難であるため考慮集合の把握は重要であ る. それが実現されることによって考慮集合が形成されていく 過程,考慮集合の傾向を把握し,より精度の高い予測やモデリ ングを行うことが可能になる. そのためにブランドや価格だけ で考慮集合の傾向を把握することも可能だが,考慮集合が形成 される要因はより多様であり,ある商品が考慮集合として選択 された条件をより詳細に把握することが求められている. そこ で本研究では,情報探索のモデルとは異なる,ECでの商品閲覧 から購買行動への流れを前提として,考慮集合として選択され た商品の選択条件語を推定する. 以下本稿では,商品選択条件 語を ISRW(Item Selected Reason Word)とする. 本研究は2 つの特徴がある. 一つ目は,同一の商品であっても選択した理 由は個人ごとに異なると考えるのが自然であるため,個人ごと に ISRWを推定する. 具体的には,商品閲覧行動モデルを個人 ごとに適用する. 2 つ目は,商品選択の条件となる語は,商品 の形状や素材,装飾特徴,感性表現など,ある商品を表現する webページ上の記述すべてが対象となりうるが,商品閲覧行動 (Item Browsing Behavier;IBB)の流れを考慮して,商品閲覧行 動の目的ごとに ISRWを推定する. 具体的には,ある条件に当 てはまるものを連続して閲覧する行動 Forcusing-IBB,単発的 に現れるが長期にわたって継続的に出現する顧客の嗜好から起 因する Preference-IBBの二つに着眼する. 本論文の構成は次の通りである. 2章で従来研究の概要と提 案手法との差異を述べる. 3章で提案手法の概要と閲覧行動モ デルの提案について述べる. 4章で実験で用いる評価データと 提案手法の実装について述べる. 5章で実験結果と考察につい て述べ,6章でまとめと今後の予定について述べる.
Annual Review of Fluid Mechanics Instabilities of Internal Gravity Wave Beams

Internal gravity waves play a primary role in geophysical fluids: They contribute significantly to mixing in the ocean, and they redistribute energy and momentum in the middle atmosphere. Until recently, most studies were focused on plane wave solutions. However, these solutions are not a satisfactory description of most geophysical manifestations of internal gravity waves, and it is now recognized that internal wave beams with a confined profile are ubiquitous in the geophysical context. We discuss the reason for the ubiquity of wave beams in stratified fluids, which is related to the fact that they are solutions of the nonlinear governing equations. We focus more specifically on situations with a constant buoyancy frequency. Moreover, in light of recent experimental and analytical studies of internal gravity beams, it is timely to discuss the two main mechanisms of instability for those beams: (a) the triadic resonant instability generating two secondary wave beams and (b) the streaming instability corresponding to the spontaneous generation of a mean flow. 131 Click here to view this article's online features: • Download figures as PPT slides • Navigate linked references • Download citations • Explore related articles • Search keywords ANNUAL REVIEWS Further A nn u. R ev . F lu id M ec h. 2 01 8. 50 :1 31 -1 56 . D ow nl oa de d fr om w w w . a nn ua lr ev ie w s. or g b y th ie rr y. da ux oi s@ en sly on . f r on 0 1/ 19 /1 8. F or p er so na l u se o nl y. FL50CH06-Dauxois ARI 24 October 2017 9:45
Lesson 1 in Design Computing Does not Have to be with Computers

This paper proposes basic design instruction as a possible setting for introducing the concept of design computing to architecture students in the fi rst year of their education. The argument is based on two viewpoints. The fi rst extends the positivistic understanding of computation to visual reasoning in general. The second recognizes visual design activity as a reasoning process. The author suggests that, in order for computation to be embedded in the ways of design thinking, an understanding of it needs to be built-in, both as concept and as practice, into learning about the design process. The study draws attention particularly to basic design instruction as a setting for design and computation to be learnt concurrently. Examples from the fi rst year curriculum at Middle East Technical University are given to illustrate the discussion.
Characterization of Bosentan Loaded Ethyl cellulose Nanoparticles by Solvent Evaporation Technique

The aim of this study was to prepare Bosentan loaded nanoparticles by Solvent Evaporation (SE) technique. Bosentan belongs to a class of drugs known as endothelin receptor antagonists (ERAs). It is a dual endothelin receptor antagonist important in the treatment of pulmonary artery hypertension (PAH). Ethyl cellulose (EC) was used as a polymer. Bosentan and ethyl cellulose were dissolved in Ethanol at various drug polymer ratios i.e. 1:1, 1:2, 1:3. Among the three formulations 1:3 formulation was considered as the best formulation with better drug content (97.43%) and entrapment efficiency (95.57%).
Bike Football Cup Bird Computer Car Dicycle Seen Unseen Hashing Model Similar ?

Hashing has been widely utilized for fast image retrieval recently. With semantic information as supervision, hashing approaches perform much better, especially when combined with deep convolution neural network(CNN). However, in practice, new concepts emerge every day, making collecting supervised information for re-training hashing model infeasible. In this paper, we propose a novel zero-shot hashing approach, called Discrete Similarity Transfer Network (SitNet), to preserve the semantic similarity between images from both “seen” concepts and new “unseen” concepts. Motivated by zero-shot learning, the semantic vectors of concepts are adopted to capture the similarity structures among classes, making the model trained with seen concepts generalize well for unseen ones. We adopt a multi-task architecture to exploit the supervised information for seen concepts and the semantic vectors simultaneously. Moreover, a discrete hashing layer is integrated into the network for hashcode generating to avoid the information loss caused by real-value relaxation in training phase, which is a critical problem in existing works. Experiments on three benchmarks validate the superiority of SitNet to the state-of-the-arts.
DETECTION AND CHARACTERIZATION OF HUMAN BOCAVIRUS IN PEDIATRIC PATIENTS WITH ACUTE GASTROENTERITIS IN CHIANG MAI , THAILAND

________________________________________________________________________ Abstract Human bocavirus(HBoV) has been reported to be associated with respiratory disease and acute gastroenteritis in patients from many countries worldwide. To determine the prevalence and genotype distribution of HBoV in Thailand, a total of 335 stool specimens collected from pediatric patients admitted to the hospitals with acute gastroenteritis in Chiang Mai, Thailand in 2015 were screened for HBoV by PCR. Twenty-one of 335 (6.3%) stool specimens were positive for HBoV. Among these, HBoV2 was the most predominant genotype (47.6%) followed by HBoV1 (42.9%) and HBoV3 (9.5%) genotypes. None of HBoV4 was detected in this study. In addition, co-infections with a number of other enteric viruses including rotavirus, norovirus, sapovirus, enterovirus, adenovirus, astrovirus, parechovirus, and cosavirus were observed in 13 of 21 (61.9%) HBoV positive patients. In conclusion, this study demonstrated that three major HBoV genotypes, HBoV1, HBoV2, and HBoV3 are cocirculating together with some other diarrhea viruses in pediatric patients in Chiang Mai, Thailand.
An analytical study for Security in IPv 6

The IPv6 protocol has solved some, but not all, of the security problems found in IPv4 networks.so in this paper we will introduce the IPv4 Limitations, the need for IPv6, the security different in IPv6, the benefits of IPv6, security regarding IPv6, the Security Considerations, IPv6 Packet Security and Transition to IPv6 .
1 Dynamically integrated spatiotemporal-based trajectory planning and control for autonomous vehicles

In the literature, the intensive research effort has been made on the trajectory planning for autonomous vehicles, while the integration of the trajectory planner with the trajectory controller is less focused. This study proposes the spatiotemporal-based trajectory planner and controller by a two-level dynamically integrated structure. In the upper level, the best trajectory is selected among a group of candidate timeparameterised trajectories, while the target vehicle ending position and velocity can be satisfied. Then the planned trajectory is evaluated by checking the feasibility when the actual vehicle dynamic motion constraints are considered. After that, the lower level trajectory controller based on the vehicle dynamics model will control the vehicle to follow the desired trajectory. Numerical simulations are used to validate the effectiveness of the proposed approach, where the scenario of an intersection and the scenario of overtaking are applied to show that the proposed trajectory controller can successfully achieve the control targets. In addition, compared with the potential field method, the proposed method based on the four-wheel independent steering and four-wheel independent driving electric vehicle shows great advantages in guaranteeing the vehicle handling and stability. Disciplines Engineering | Science and Technology Studies Publication Details B. Li, H. Du, W. Li & B. Zhang, "Dynamically integrated spatiotemporal-based trajectory planning and control for autonomous vehicles," IET Intelligent Transport Systems, vol. 12, (10) pp. 1271-1282, 2018. This journal article is available at Research Online: https://ro.uow. edu.au/eispapers1/2124
Radio Virtual Machine Virtual Machine for Reconfigurable Radio

Reconfigurable Radio assumes that the radio hardware platform is reconfigurable in such a way that the essential radio characteristics (carrier frequencies, spectrum bandwidth, modulation technique, coding technique, output power levels, etc.) can be changed according to the flexibility of hardware platform that is defined by manufacturers. Resultant radio hardware platforms are heterogeneous by nature and include computational elements with different level of programmability or reconfigurability. This paper addresses the problem of software portability and its application to the reconfigurable platforms. Main contribution of this article is to present a novel architecture of the virtual domain-specific machine, namely, Radio Virtual Machine (RVM), which provides an efficient implementation of calculations related to radio signal processing in hardware platforms of different nature.
Imprecision in WCET estimates due to library calls and how to reduce it (WIP paper)

One of the main difficulties in estimating the Worst Case Execution Time (WCET) at the binary level is that machine instructions do not allow inferring call contexts as precisely as source code, since compiler optimizations obfuscate control flow and type information. On the other hand, WCET estimation at source code level can be precise in tracking call contexts, but it is pessimistic for functions that are not available as source code. In this paper we propose approaches to join binary-level and source-level analyses, to get the best out of both. We present the arising problems in detail, evaluate the approaches qualitatively, and highlight their trade-offs.
Vista.ue at SemEval-2019 Task 5: Single Multilingual Hate Speech Detection Model

This paper shares insight from participating in SemEval-2019 Task 5. The main propose of this system-description paper is to facilitate the reader with replicability and to provide insightful analysis of the developed system. Here in Vista.ue, we proposed a single multilingual hate speech detection model. This model was ranked 46/70 for English Task A and 31/43 for English Task B. Vista.ue was able to rank 38/41 for Spanish Task A and 22/25 for Spanish Task B.
HHU at SemEval-2019 Task 6: Context Does Matter - Tackling Offensive Language Identification and Categorization with ELMo

We present our results for OffensEval: Identifying and Categorizing Offensive Language in Social Media (SemEval 2019 - Task 6). Our results show that context embeddings are important features for the three different sub-tasks in connection with classical machine and with deep learning. Our best model reached place 3 of 75 in sub-task B with a macro F_1 of 0.719. Our approaches for sub-task A and C perform less well but could also deliver promising results.
Team Ned Leeds at SemEval-2019 Task 4: Exploring Language Indicators of Hyperpartisan Reporting

This paper reports an experiment carried out to investigate the relevance of several syntactic, stylistic and pragmatic features on the task of distinguishing between mainstream and partisan news articles. The results of the evaluation of different feature sets and the extent to which various feature categories could affect the performance metrics are discussed and compared. Among different combinations of features and classifiers, Random Forest classifier using vector representations of the headline and the text of the report, with the inclusion of 8 readability scores and few stylistic features yielded best result, ranking our team at the 9th place at the SemEval 2019 Hyperpartisan News Detection challenge.
YUN-HPCC at SemEval-2019 Task 3: Multi-Step Ensemble Neural Network for Sentiment Analysis in Textual Conversation

This paper describes our approach to the sentiment analysis of Twitter textual conversations based on deep learning. We analyze the syntax, abbreviations, and informal-writing of Twitter; and perform perfect data preprocessing on the data to convert them to normative text. We apply a multi-step ensemble strategy to solve the problem of extremely unbalanced data in the training set. This is achieved by taking the GloVe and Elmo word vectors as input into a combination model with four different deep neural networks. The experimental results from the development dataset demonstrate that the proposed model exhibits a strong generalization ability. For evaluation on the best dataset, we integrated the results using the stacking ensemble learning approach and achieved competitive results. According to the final official review, the results of our model ranked 10th out of 165 teams.
Team Howard Beale at SemEval-2019 Task 4: Hyperpartisan News Detection with BERT

This paper describes our system for SemEval-2019 Task 4: Hyperpartisan News Detection (Kiesel et al., 2019). We use pretrained BERT (Devlin et al., 2018) architecture and investigate the effect of different fine tuning regimes on the final classification task. We show that additional pretraining on news domain improves the performance on the Hyperpartisan News Detection task. Our system ranked 8th out of 42 teams with 78.3% accuracy on the held-out test dataset.