Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimization of Linear Permanent Magnet ( PM ) Generator with Triangular-Shaped Magnet for Wave Energy Conversion using Finite Element Method

This paper presents the design optimization of linear permanent magnet (PM) generator for wave energy conversion using finite element method (FEM). A linear PM generator with triangular-shaped magnet is proposed, which has higher electromagnetic characteristics, superior performance and low weight as compared to conventional linear PM generator with rectangularshaped magnet. The Individual Parameter (IP) optimization technique is employed in order to optimize and achieve optimum performance of linear PM generator. The objective function, optimization variables; magnet angle, M , the pole-width ratio, _ ⁄ , and split ratio between translator and stator, _ ⁄ , and constraints are defined. The efficiency and its main parts; copper and iron loss are computed using time-stepping FEM. The optimal values after optimization are presented which yields highest efficiency.
Understanding and Improving Security and Privacy in Multi-User Smart Homes: A Design Exploration and In-Home User Study

Smart homes face unique security, privacy, and usability challenges because they are multi-user, multi-device systems that affect the physical environment of all inhabitants of the home. Current smart home technology is often not well designed for multiple users, sometimes lacking basic access control and other affordances for making the system intelligible and accessible for all users. While prior work has shed light on the problems and needs of smart home users, it is not obvious how to design and build solutions. Such questions have certainly not been answered for challenging adversarial situations (e.g., domestic abuse), but we observe that they have not even been answered for tensions in otherwise functional, non-adversarial households. In this work, we explore user behaviors, needs, and possible solutions to multi-user security and privacy issues in generally non-adversarial smart homes. Based on design principles grounded in prior work, we built a prototype smart home app that includes concrete features such as location-based access controls, supervisory access controls, and activity notiﬁcations, and we tested our prototype though a month-long in-home user study with seven households. From the results of the user study, we re-evaluate our initial design principles, we surface user feedback on security and privacy features, and we identify challenges and recommendations for smart home designers and researchers.
Chapter 3 Identifying senses of particles in verb-particle constructions

In order to attain broad coverage understanding, a system need not only identify multiword expressions such as verb-particle constructions (VPCs), but must compute their meaning. It is not plausible to hand enumerate all possible combinations, although WordNet is an admirable start. This chapter focuses on the identification of senses of particles in VPCs in order to compute the meanings of VPCs – using information obtained from existing lexical resources such as WordNet, and augmenting it with additional knowledge based on linguistic investigation of VPCs identified in terms of generalizations encoded in the TRIPS ontology.The approach consists of first determining compositionality of a VPC based on the information present in WordNet, and then assigning a relevant sense to the particle in a compositional VPC based on the sense classes we have identified and encoded in the TRIPS’ computational lexicon. Contributions of the described work are twofold: (1) A discussion of senses of particles in VPCs and corresponding generalizations makes a linguistic contribution. (2)We show how linguistic knowledge can be used to automatically parse sentences containing VPCs and obtain a semantic representation of them. An advantage of the described approach is that VPCs not explicitly found in lexica can be identified and semantically interpreted.
Fault Classification and Location in Transmission Lines Using Traveling Waves Modal Components and Continuous Wavelet Transform ( CWT )

Accurate fault classification and localization are the bases of protection for transmission systems. This paper presents a new method for classifying and showing location of faults by travelling waves and modal analysis. In the proposed method, characteristics of different faults are investigated using Clarke transformation and initial current traveling wave; then, appropriate indices are introduced to identify different types of faults. Continuous wavelet transform (CWT) is employed to extract information of current and voltage travelling waves. Fault location and classification algorithm is being designed according to wavelet transform coefficients relating to current and voltage modal components. The performance of the proposed method is tested for different fault conditions (different fault distance, different fault resistances, and different fault inception angles) by using PSCAD and MATLAB with satisfactory results.
Poster : Statistical coding scheme for the protection of cryptographic systems against brute-force attack

A new algorithm for secure communication, with statistical encoders and decoders is introduced to protect cryptographic algorithms from brute-force attacks. In our proposed approach, even incorrect plain texts decrypted with wrong keys can have semantically/synthetically fine meaning. That is, every keys can be used as a key in cryptanalysis. Because of this, malicious people cannot distinguish correct plain texts from many incorrect plain texts.
A ROBUST OPTIMIZED FEATURE SET BASED AUTOMATIC CLASSIFICATION OF ALZHEIMER’S DISEASE FROM BRAIN MR IMAGES USING K-NN AND ADABOOST

For individuals suffering from some cognitive impairment, treatment plans will be greatly help patients and medical practitioners, if early and accurate detection of Alzheimer’s disease (AD) is carried out. Brain MR Scans of patients’ with health history and supportive medical tests results can lead to distinguish between Healthy/ Normal Controls (NC), Mild Cognitive Impairment (MCI) and AD patients. However manual techniques for disease detection are labour intensive and time consuming. This work is towards the development of Computer Aided Diagnosis (CAD) tool for Alzheimer’s disease detection and its classification into the early stage of AD i.e. MCI and later stage –AD. The paper is about selection of robust optimized feature set using combination of forward selection and/or backward elimination method with K-NN classifier and validation of results with features selected (using forward selection method); with Ada-boost for improved classification accuracy. The features are extracted on Gray Level Cooccurrence Matrix (GLCM). The experimentation is based on Public Brain Magnetic Resonance datasets named Open Access Series of Imaging Studies (OASIS) [7] with patients diagnosed with NC, MCI and AD. The four models considered for automatic classification are – i. Abnormal vs. Normal; ii. AD vs. MCI; iii. MCI vs. NC and iv. AD vs. NC. Feature set optimized using K-NN and validated with AdaBoost has given improved classification accuracy for each model. The output of developed CAD system is compared with Radiologists opinion for test images and has shown 100% match between the output of computer algorithm and experts opinion for some important models under consideration.
Enhancements for Reactive Planning – Tricks and Hacks

Behavior based action selection is utilized for agents residing in complex and unpredictable virtual worlds. The techniques based on reactive planning, where rules are organized into a hierarchy where single plans consist of if-then rules ordered by priority, are popular not only for their simplistic design but also for the possibilities they provide in modeling believable behaving agents. In this paper we propose simple and easy to integrate enhancements for the if-then rule based behavior models, providing the designer with more possibilities to control the designed behavior and to overcome the by us observed limitations of the basic reactive planning concept. The result is an improved formalism for reactive rules, which could be utilized for more believable behavior modeling. The proposed concept upgrades are designed to be backward compatible with the basic concept.
CONSERVATION PRIORITIES AND PERIPHERAL SPECIES IN THE SOUTH OKANAGAN: CONSIDERATIONS FOR A PROPOSED NATIONAL PARK

Setting conservation priorities is critical if we are to be more effective in protecting species. In the South Okanagan, current conservation effort is strongly weighted to species occurring at the northern limit of their range because they cross a political boundary and are considered rare in British Columbia and Canada. A national park has been proposed for the South Okanagan in order to protect this nationally unique ecosystem and its corresponding flora and fauna. To examine current conservation practices in the South Okanagan I interviewed various stakeholders and government representatives on where they think conservation priorities should be allocated with regard to the proposed national park. The reasons given for why peripheral species should be allocated resources included: i) locally rare species help maintain genetic diversity; ii) locally rare species are charismatic and attract tourism; and iii) Canada cannot rely on the United States to protect core ranges, so we should protect what we have. Some responses lie at the other end of this spectrum, with noted concern for the effectiveness and wastefulness of allocating scarce resources to species irregularly occurring at the edge of their range. These proponents would rather see money spent on monitoring all species. If a South Okanagan national park is to be successful in terms of halting anthropogenic species extinctions and protecting continuously peripheral populations, recognition of stakeholder values and biological shortcomings for protecting those species must be considered.
ISOLATING INFORMATIVE BLOCKS FROM LARGE WEB PAGES USING HTML TAG PRIORITY ASSIGNMENT BASED APPROACH

Searching useful information from the web, a popular activity, often involves huge irrelevant contents or noises leading to difficulties in extracting useful information. Indeed, search engines, crawlers and information agents may often fail to separate relevant information from noises indicating significance of efficient search results. Earlier, some research works locate noisy data only at the edges of the web page; while others prefer to consider the whole page for noisy data detection. In our paper, we propose a simple priority-assignment based approach with a view to differentiating main contents of the page from the noises. In our proposed technique, we first make partition of the whole page into a number of disjoint blocks using HTML tag based technique. Next, we determine a priority level for each block based on HTML tags priority while considering aggregate priority calculation. This assignment process gives a priority value to each block which helps rank the overall search results in online searching. In our work, the blocks with higher priority are termed as informative blocks and preserved in database for future use, whereas lower priority blocks are considered as noisy blocks and are not used for further data searching operation. Our experimental results show considerable improvement in noisy block elimination and in online page ranking with limited searching time as compared to other known approaches. Moreover, the obtained accuracy from our approach by applying the Naive Bayes text classification method is about 90 percent, quite high as compared to others.
The relation between knowledge transfer and productivity in knowledge work

Abstract Within the modern ICT-enabled knowledge work context, questions related to access to information and knowledge-sharing practices have received growing research attention. However, there is still surprisingly little empirical research exploring the actual impact of effective knowledge transfer to work productivity. The purpose of this paper is to fulfil this research gap and empirically study whether there are any differences in subjective work productivity based on how the knowledge worker perceives the level of information flow and knowledge transfer within the organisation. Furthermore, the aim is to determine whether there are differences between the extent to which the positively experienced information flow and knowledge transfer impact experienced work productivity. Through the survey method, data were collected from 998 knowledge workers from Finland in various sizes of organisations. The quantitative data were analysed using SPSS software descriptive statistics, correlations and U-tests. The practical value of the study is in the analysis results. The paper presents the value of information flows and knowledge transfer to knowledge work productivity. This increased understanding will help managers to evaluate the effects of investing in supporting information flows and knowledge transfer within their organisations.
UNCERTAINTY QUANTIFICATION IN DURABILITY ANALYSIS OF CEMENTITIOUS MATERIALS UNDER SULFATE ATTACK

This paper develops a probabilistic methodology for quantifying the uncertainty in assessing the durability of cement-based structures under fluctuating environmental conditions. Sulfate attack is one of the major degradation processes for concrete vaults used for the storage of low level nuclear wastes. In this study, ingression of sulfate ions is chosen as the primary degrading phenomenon. The numerical modelling includes diffusion, chemical reaction and damage accumulation. The ultimate objective of the research is to compute the probability of reaching a degradation measure as a function of time, while accounting for various sources of uncertainty – physical variability, data uncertainty, and model uncertainty. Existing numerical methods for incorporating the sources of uncertainty in the numerical model are reviewed.
Molecular isolation , cloning and sequencing of chicken insulin-like growth factor 1 ( IGF-1 ) gene from high producing exotic breed to produce transgenic chickens of native breeds in Egypt

Molecular analysis is an easier means to identify and isolate a specific gene which has imperative function for growth, body composition, fat deposition, metabolic and skeletal traits as well as the molecular genetics selection on individual genes is a very efficient method to genetically improve economically important traits in chickens. Insulin-like growth factor 1 (IGF1) is a member of a heterogeneous group of peptides with important growth-promoting effects in vitro as well as in vivo. It plays a fundamental role in postnatal chicken growth as a major mediator through which growth hormone exerts its biological effects. In this study, total RNA was isolated from (Cobb 500 breed) liver samples at 50 weeks age from national poultry company in Egypt. cDNA was produced by reverse transcriptase-polymerase chain reaction (RT-PCR). Standard PCR was carried on using two flanking primers containing HindIII and EcoRI restriction enzymes to generate the whole length of IGF-1 gene. A PCR product of 490bp, including the open reading frame of IGF-1 gene corresponding to the expected theoretical product size, was successfully amplified and double digested with HindIII and EcoR1 and cloned into same Restriction enzymes digested PCR3.1 mammalian expression vector. Interestingly, the cloned sequence was confirmed by DNA sequencing which reveals that, it is cloned in frame position and 99% matching except one nucleotide due to the heterozygous of isolated IGF-1 cDNA. In the present study we report the isolation, molecular cloning and sequencing of full-length IGF-1 cDNA from chicken liver, encoding the IGF-1 protein, can be used as a candidate gene in transgenic Egyptian native breed production based on the IGF1 protein of exotic high producing chicken population and may give a tool in continuous improvements of the chicken industry concerning a native breed in Egypt.
An Improved LEACH-C Algorithm for Energy Efficiency in WSN Routing

this paper considered a multi-objective LEACHC algorithm in the selection of Cluster Head (CH) in such a way so that its energy is used uniformly with load balancing among clusters for delayed disintegration of network. LEACH-C algorithm based single objective clustering approach has been replaced by multi-objective clustering approach where we not only considered the residual energy of nodes but the size of cluster in creating a cluster structure. The improved LEACH-C protocol has been compared with random LEACH and Max Energy LEACH or existing LEACH-C algorithm for energy equi-distribution and load balancing among clusters. Wireless sensor network (WSN) is simulated using a MATLAB programming and power consumption algorithms take into consideration all aspects of power consumption in the operation of the node. The modified LEACH-C routing protocol shows improvements in lifetime as well as in network disintegration criterion.
Model-based interface code generation : an extensible framework for automatic generation of wrapper code

Implementation and maintenance of interface wrapper code are relatively mechanical tasks. These tasks are repetitive, laborious, and error prone including numerous copy-paste actions and manual modifications from previous implementation samples. This report describes design, implementation, and deployment of an extensible framework for automatic generation of wrapper code. The framework, which is based on the Model-Driven Architecture, consists of parser, model-to-model transformer, and model-to-code transformer. The code generation framework described in this report is more suitable for using in a C# . NET environment than other existing technologies like Eclipse xtext/xtend. It is extensible for multiple domain specific languages and code artifacts, as well as simple to use with Visual Studio tool.
FOR DETERMINATION OF THE VALUE OF ACTIVATION ENERGY AT HOT FORMING

Activation energy at hot forming is an important material constant, which depends on chemical composition and microstructure of the given material. It is used for example for prediction of coordinates of stress peak, i.e. of maximal flow stress and beginning of dynamic recrystallisation of material formed under the given thermal-mechanical conditions. Its determination is made particularly with use of plastometric test. In this case torsion tests were performed on SETARAM plastometer and tests by uniaxial compression on plastometer Gleeble 3800 with use of the samples manufactured from low-alloyed steel 42CrMo4. Comprehensive set of torsion tests was performed at deformation temperatures from 800 to 1100 °C and at selected strain rates ranging from 0.02 to 2.3 s -1 . Compression tests were realised with use of analogical parameters, however, the range of applied strain rates was moreover extended by the values 12 and 60 s -1 , which are practically unachievable on torsion plastometer. Activation energy was determined for each set of data always by regression analysis of the obtained peak stresses in dependence on the on temperature and strain rate. Its values were determined separately from the data obtained by torsion tests and separately from the data obtained by compression tests, not only at analogical parameters of forming, but also with inclusion of the results obtained with broader range of applied strain rates. The objective of the realised experiments was to verify how deeply the chosen plastometric methods and range of deformation conditions influence calculation of activation energy of the given steel at hot forming, which is very important from the viewpoint of methodology.
Information recovery in ptychographic coherent diffraction imaging

Ptychographic coherent diffraction imaging has been used to overcome the finite space-bandwidth product in classical lens-based microscopy and solve the phase problem in lens-less imaging. While ptychography harnesses data redundancy to recover information about object, illumination and coherence with theoretically unlimited field of view, practically this ability is limited by the computational memory available. Here we present data compression strategies that allow for data reduction by an order of magnitude and promise to find application in memory-limited ptychograpy.
TRPM 7-mediated Ca 2 + Signals Confer Fibrogenesis in Human Atrial Fibrillation

Rationale—Cardiac fibrosis contributes to pathogenesis of atrial fibrillation (AF), which is the most sustained arrhythmia and a major cause of morbidity and mortality. Although it has been suggested that Ca2+ signals are involved in fibrosis promotion, the molecular basis of Ca2+ signaling mechanisms and how Ca2+ signals contribute to fibrogenesis remain unknown. Objective—To determine the molecular mechanisms of Ca2+-permeable channel(s) in human atrial fibroblasts, and to investigate how Ca2+ signals contribute to fibrogenesis in human AF. Methods and Results—We demonstrate that the transient receptor potential melastatin related 7 (TRPM7) is the molecular basis of the major Ca2+-permeable channel in human atrial fibroblasts. Endogenous TRPM7 currents in atrial fibroblasts resemble the biophysical and pharmacological properties of heterologous expressed TRPM7. Knocking down TRPM7 by small hairpin RNA (shRNA) largely eliminates TRPM7 current and Ca2+ influx in atrial fibroblasts. More importantly, atrial fibroblasts from AF patients show a striking upregulation of both TRPM7 currents and Ca2+ influx and are more prone to myofibroblast differentiation, presumably due to the enhanced expression of TRPM7. TRPM7-shRNA markedly reduced basal AF fibroblast differentiation. Transforming growth factor β1 (TGF-β1), the major stimulator of atrial fibrosis, requires TRPM7-mediated Ca2+ signal for its effect on fibroblast proliferation and differentiation. Furthermore, TGF-β1 induced differentiation of cultured human atrial fibroblasts is well correlated with an increase of TRPM7 expression induced by TGF-β1. Conclusions—Our results establish that TRPM7 is the major Ca2+-permeable channel in human atrial fibroblasts, and likely plays an essential role in TGF-β1-elicited fibrogenesis in human AF.
Topological Venn Diagrams and Graphs

This paper is an attempt to expound Venn diagrams and its applications in Topology and Graph Theory. John Venn introduced Venn diagrams in 1880. Venn diagrams can be called as Eulerian Circles. Euler invented this in the 18 th century. Venn diagram consists of curves and circles. Venn diagrams are similar to Euler diagrams. Edwards discusses the dual graph of a Venn diagram is a maximal planar subgraph. Edwards-Venn diagrams are topologically equivalent to diagrams with graphs. 2D and 3D Venn diagrams consist of labeled simple closed curves. 3D Venn diagrams and 3D Euler diagrams are all combinations of surface intersections. In brief this paper will give a vivid picture of Venn diagrams and its close relationship with Topology and Graph Theory.