Miracle-dz/UniFAR-FTUs huggingface dataset:
DNA Indexing & Searching Human Authentication using STR Locus based on PCR Process

DNA Indexing & Search Human Authentication System works on bases of DNA profiling. It contains a DNA Data Bank which has DNA Profiles of civilization. DNA Profile stored with DNA STR Locus or DNA sample and necessity person’s information. These samples are stored in database by performing algorithmic procedure, it is the major task of the system which is not stored a DNA sample in physically but it stored with digitize unique DNA signature. It also manages the DNA Data Bank and is responsible for developing, providing, and supporting this Program to federal, state, and local crime laboratories in our country and selected international law enforcement crime laboratories to foster the exchange and comparison of forensic DNA evidence from violent crime investigations. The DNA Data Bank Unit also provides administrative management and support to the police or crime investigation departments for various advisory boards, Forensic Science, Department of Justice (DOJ) grant programs, and legislation regarding DNA.  Salient features of this system to resolve.
Understanding implicit social context in electronic communication

Artificial Intelligence (Al) has shown competence in helping people with complex cognitive decisions like air traffic control and playing chess. The goal of this work is to demonstrate that Al can help people with social decisions. In this work Artificial Intelligence of Social Networks is used to improve human-human communication, recognizing the social characteristics of human relations in order to achieve a more natural online communication interface. Can a computer learn to understand the value of communication? It is shown here that a first attempt at social context classification performs with almost 70% reliability. Could a computer use this to help a person relate to other people through technology? The addition of social context to an email interface is shown to have a positive effect in a user's online communication behavior. Email is a tool that people use practically every day, making an implicit statement about their relationships with other people, and providing an opportunity for a computer to learn about their social network. Furthermore, over the years people have come to utilize and depend on email more in their daily lives, but the tool has hardly changed to help people deal with the overwhelming amount of information. Many of the social cues that allow people to naturally function with their social network are not inherent or obvious in Computer Mediated Communication (CMC). This work offers automatic social network analysis as a means to bring these cues to CMC and to foster the user's coherent understanding of the people and resources of their communication network. Thesis Supervisor: Ted Selker Associate Professor, MIT Program in Media Arts and Sciences The author thanks the Eircom Fellows Program for their support of her research.
TOWARD THE DEVELOPMENT OF COMPUTATIONAL AIDS FOR OBTAINING A FORMAL SEMANTIC DESCRIPTION OF ENGLISH

Abstract : Projected automatic and semi-automatic routines for processing transcripts of Webster's Seventh New Collegiate Dictionary (W7) and The New Merriam-Webster Pocket Dictionary (MPD) are briefly described. Among the outputs of these routines will be an approximation to a set of semantic primitives for English, hierarchically ordered lists of semantic classifiers, and semantic fields. The results of a study of productive lexical processes (both affixally marked and affixally unmarked) are reported, and its relationship to recent work in generative grammar is noted. Studies of several aspects of W7 definitions are described, with particular emphasis given to defining formulas. All of these studies have had the dual objective of clarifying the criteria by which the outputs of the routines for processing the W7 and MPD transcripts should be judged as well as contributing to the development of the routines. (Author)
Encouraging coupled views for visualization exploration

Scientific visualization, especially visualization exploration, enables information to be investigated and better understood. Exploration enables hands-on experimentation with the displayed visualizations and the underlying data. Most exploration techniques, by their nature, generate multiple realizations and many data instances. Thus, to best understand the information in coincident views, the manipulation information within one view may be 'directed' to other related views. These multiple views may be described as being closely coupled. Within this paper we advocate the use of coupled views for scientific visualization exploration. We describe, some key concepts of coupled views for visualization exploration and present how to encourage their use. The key concepts include: the scope of the correlation (between two specific views or many realizations), who initiates the correlation (whether the user or the system) and issues about 'what is correlated' (objects with a view, or the whole viewport).
C-reactive Protein Gene G1059C Polymorphism and Atrial Fibrillation- Genetic and Functional Studies

Background Inflammation plays an important role in AF pathogenesis. Whether genetic variant in the C-reactive protein (CRP) gene predisposes to AF, and molecular effects of CRP on atrial myocytes and fibroblasts are unknown. Objective To evaluate association between CRP gene G1059C polymorphism and non-familial atrial fibrillation (AF), and effect of CRP on atrial myocytes and fibroblasts. Methods We performed genetic association study to investigate association between CRP gene G1059C polymorphism and non-familial AF. We used whole cell patch-clamp and reverse-transcription polymerase chain reaction to investigate the effect of CRP on the transmembranic ionic currents and expression of procollagens in atrial myocytes and fibroblasts, respectively. Results Two-hundred and forty-three patients with non-familial AF and 348 controls were recruited. AF patients had a higher plasma CRP level (3.87±3.59 vs 2.91±3.30 mg/L, P=0.0008). The 1059C variant was associated with a lower CRP level, and a lower risk of AF (OR 0.54 [0.30-0.97] and 0.55 [0.32-0.94] for dominant and additive models, respectively, after multivariate adjustment). CRP significantly increased the inward L-type calcium channel, without significant change on T-type calcium current and other outward potassium currents in HL-1 atrial myocytes. CRP did not affect the expressions of type I alpha 1 (COL1A1), type III alpha 1 (COL3A1) and type 1 alpha 2 2 (COL1A2) procollagens in atrial fibroblasts. Conclusions CRP gene G1059C polymorphism determines the basal level of CRP and the risk of common AF. The mechanism may be through an augmented inward calcium current by CRP in atrial myocytes, but not through atrial fibrosis.
Evaluation of sand-based stormwater filtration system for groundwater recharge wells

Groundwater recharge wells have proven effective in augmenting and improving the quality of groundwater, but clogging remains a serious constraint in the absence of properly designed recharge filters. A laboratory study was undertaken in a PVC column of 22.5 cm diameter and 120 cm length to evaluate the efficiency of coarse sand (CS) of three particle sizes ranging between 0.35 and 1.0 mm as the top layer of a recharge filter for seven influent sediment concentrations of 250–3,000 mg/l. The performance was evaluated in terms of spatial movement of sediments, removal efficiency, recharge rates and clogging time. The results indicated that more than 60% suspended solids were entrapped in the upper 10 cm layer of CS, the removal efficiency improved with increasing thickness of the CS layer and the recharge rates declined sharply for influent concentrations of more than 1,000 mg/l. The study suggests use of larger particle size CS and reducing sediment load of inflow water. Field adaptation of these findings involves use of CS beds of 0.7–1.0 mm particle size and minimum 75 cm thickness as the top layer in recharge filters and providing a sediment tank or biological filters near the recharge structures to reduce sediment load of run-off water before entering the filter bed.
ADAPTIVE PENDULUM MASS DAMPER FOR THE CONTROL OF STRUCTURAL VIBRATIONS

Incorporating adjustment mechanisms to compensate for de-tuning in traditional tuned mass dampers is essential for the advancement of this technology. In this paper, experimental and simulation results on the control of structural vibrations using an adaptive pendulum mass damper are presented. The adaptive pendulum mass damper is a spherical pendulum augmented with a tuning frame to adjust its length and two adjustable air dampers connected to the mass for achieving the damping adjustment. The mechanical adjustments are implemented using three independent stepper motors, one micro-controller and three drives. The mass damper is used to control the vibration responses of a bench-scale two-story model structure with sufficiently long fundamental period representative of flexible structures such as towers. The basic architecture of the system proposed consists of two components; identification and control, one followed by the other in that order. The identification is carried out using traditional Fourier methods and a second-order blind identification method in the time-domain. The control phase consists of position control based on the identified frequency from the identification phase. The paper focuses on the hardware and software aspects of the real-time implementation of this adaptive mass damper. The identification methods used in this study rely only on acceleration measurements collected from high accuracy-low frequency accelerometers mounted on the structure, and do not utilize the excitation information. This study is primarily intended to demonstrate the feasibility of employing adaptive pendulum mass damper designs to enhance the robustness of passive tuned mass dampers to structural, environmental and design changes.
Computer Program Plagiarism Detection: The Limits of the Halstead Metric

Plagiarism detection is an increasingly important issue in educational environments. This article employs two alternative metrics in the identification of program similarity. The first is the Halstead metric drawn from the discipline of software science. The second is an ad hoc metric drawn from program grading experience, and identified by means of factor analysis. The ad hoc metric proves to be more useful in identical-task environments. Possible explanations for, as well as some larger implications of, this result are considered.
OCEAN ACOUSTIC TOMOGRAPHY: A MISSING ELEMENT OF THE OCEAN OBSERVING SYSTEM

Ocean acoustic tomography now has a long history with many observations and experiments that highlight the unique capabilities of this approach to detecting and understanding ocean variability. Examples include observations of deep mixing in the Greenland Sea, mode-1 internal tides radiating far into the ocean interior (coherent in time and space), relative vorticity on multiple scales, basin-wide and antipodal measures of temperature, barotropic currents, coastal processes in shallow water, and Arctic climate change. Despite the capabilities, tomography, and its simplified form thermometry, are not yet core observations within the Ocean Observing Systems (OOS). These observing systems could benefit greatly from applied acoustical oceanography, and both the world’s climatic circumstance and the difficulty in ocean observation argue that all available techniques should be implemented. A perception that the existence of the Argo float system obviates the need for the acoustical observations has been shown to be false; observations of ocean variability by tomography are distinct from those of floats or gliders. The growing application of acoustical measurements as part of the observing system (e.g., IQOE or UACE2017 4th Underwater Acoustics Conference and Exhibition
EFFECTIVENESS & ECONOMY OF SAWDUST WOOD ADSORBENTS IN REMOVING ANIONIC DYES OF AQUEOUS SOLUTIONS

Adsorption of methyl orange (MO) from the aqueous solution on a low-cost adsorbent made of sawdust wood (SW) is studied experimentally. In the current research, a comparative study has been conducted between the natural sawdust wood (SW) and the activated sawdust wood (ASW). Conditions of experimental study were included the followings: 10 ppm of methyl-orang, pH=6 and a dosage in the range of 0.5 2 gm for different sizes of sawdust. During the study, Fourier-transform infrared spectroscopy-(FTIR) as well as (UV/V) is spectroscopy techniques were used. Results obtained indicate that the removal efficiency of methyl orange at 25 ± 3 C exceeded 38.7%. A good fit for equilibrium data was obtained as per Langmuir model (R> 0.99). Maximum adsorption capacity of MO on ASW is 1.8 mg g-1. Results analysis of the activated sawdust waste show more a potential effectiveness as cheap adsorbent for the dyes removal from industrial wastewater.
Immigration and Economic Growth : Further Evidence for Greece

The present paper examines the relationship between immigration and economic growth for Greece. In the empirical analysis of this paper, Johansen cointegration and Gregory and Hansen tests are applied to examine the long-run relationships and structural change of variables respectively . A vector error correction model VAR is used in order to test the relationship between the number of immigrants and economic growth. The results of Granger causality tests indicate a bidirectional relationship between economic growth and immigration.
DEIM Forum 2016 C 4-6 Query Suggestion for Helping Struggling Search

Search engine users often struggle to find the relevant information for their information need by reformulating their queries many times. Since many queries during struggling search are failed and sparse, the existing query suggestion methods often fail to generate effective query suggestions for struggling search. In this paper, we propose a method to generate effective query suggestions aiming to help struggling search. The core is identifying struggling component of on-going struggling session and mining the effective representations of it. The struggling component is the semantic unit of information need for which the user struggled to find an effective representation during the struggling session. The proposed method first identifies the struggling component of given on-going struggling session and mines the sessions containing the identified struggling component from a query log to build a struggling flow graph. The struggling flow graph records the struggling reformulation behaviors of multiple users for the given struggling component. The experimental results demonstrate that the proposed method outperforms the existing algorithm in terms of MRR@10 and nDCG@10.
Konya bölgesi koyunlarında Maedi-Visna Virus enfeksiyonu üzerine serolojik araştırma

Bulgular: 1343 adet kan serumunun 39 tanesinin (%2.90) MVV antikor varlığı yönünden pozitif olduğu tespit edildi. İşletmelere göre seropozitiflik oranlarının %0.85 ve %13.33 arasında olduğu belirlendi. Sonuçlar ırklara göre incelendiğinde; Akkaraman ırkı koyunların 36’sı (%2.68) ve Morkaraman ırkı koyunların 3’ü (%0.22) pozitif olarak tespit edildi. Cinsiyete göre seropozitiflik oranları değerlendirildiğinde; 33 dişi (%2.45) ve 6 erkek (% 0.44) hayvan seropozitif tespit edildi. Seropozitif olarak tespit edilen 33 dişi koyunun 30’u Akkaraman, 3’ünün ise Morkaraman olduğu belirlendi. Seropozitif 6 erkek koyunun ise Akkaraman ırkına ait olduğu tespit edildi. Seropozitif 39 koyunun 1-2.5 yaşında olduğu belirlendi.
Neural Relation Extraction for Knowledge Base Enrichment

We study relation extraction for knowledge base (KB) enrichment. Specifically, we aim to extract entities and their relationships from sentences in the form of triples and map the elements of the extracted triples to an existing KB in an end-to-end manner. Previous studies focus on the extraction itself and rely on Named Entity Disambiguation (NED) to map triples into the KB space. This way, NED errors may cause extraction errors that affect the overall precision and recall.To address this problem, we propose an end-to-end relation extraction model for KB enrichment based on a neural encoder-decoder model. We collect high-quality training data by distant supervision with co-reference resolution and paraphrase detection. We propose an n-gram based attention model that captures multi-word entity names in a sentence. Our model employs jointly learned word and entity embeddings to support named entity disambiguation. Finally, our model uses a modified beam search and a triple classifier to help generate high-quality triples. Our model outperforms state-of-the-art baselines by 15.51% and 8.38% in terms of F1 score on two real-world datasets.
A 15 b electromechanical sigma-delta converter for acceleration measurements

Precision accelerometers for applications such as inertial navigation and guidance, tilt measurement and low-level vibration monitoring can be characterized by shown specifications . Drawbacks of classical electromagnetic servo-accelerometers (fabrication cost, power consumption and shock resistance) are overcome by using a bulk micromachined capacitive accelerometer and a CMOS interface circuit. <<ETX>>
Recommender System Algorithms

Within the Industrial Engineering program, students are finding it increasingly difficult to select courses which both maximize their academic standing, while suiting their more professional objectives. Without question, a good many of these students pursue courses that either do not interest them or courses which do coincide well with their respective academic and personal repertoires. Nonetheless, present-day technological systems are available to properly address this reality and alleviate such burdens for prospective students. With the usage of recommender system algorithms, this thesis will establish whether or not a system can be built which can successfully guide students in selecting their future courses to fit their aforementioned objectives. Present-day recommender systems are widely used on the web, especially in e-commerce applications. For instance, customers wishing to purchase new items on these shopping sites can be recommended products. As a result, this leads to an increase in sales vis-à-vis the use of mathematical algorithms that compare an active customer’s history to previous history to determine correlations, and, finally, generate recommendations. Most importantly, this study shall elucidate the widely used recommender algorithms that outline the system that was built to recommend electives for Industrial Engineering students, based on their academic history. Furthermore, this report will identify which recommender algorithm facilitates the most accuracy and performance. To conclude, we shall identify areas of improvement in order to continuously improve the efficacy of recommender systems in general and for the purposes of this report.
Differences in the Linkage between Socio-economic Conditions and Child Health between Ethnic Groups in Rural Guatemala

This paper investigates the differences in the links between the socio-economic conditions and child health of ethnic groups in rural Guatemala. Variations in the links are observed within indigenous populations as well as between ethnic groups. To observe the differences within indigenous populations, groups are classified according to the language spoken in the home and the area of residence. Indigenous people who speak Spanish in the home, that is, those who share relatively more ladino features, have similar tendencies as ladinos regarding the correlation between socio-economic conditions and child health in some areas. Improvements in economic status are likely to contribute to improvements in ladino children’s health status. The effect is relatively low or non-existent for indigenous people, particularly for those who share more indigenous features. The likely explanation is that indigenous people who share relatively more indigenous features use household resources inefficiently for child health compared to the ladino population and indigenous people who share relatively more ladino features. Because ethnic groups tend not to reside in the same area, one aspect of the variations in the links between socio-economic conditions and child health among ethnic groups is reflected by the different regional areas of residence.
Dynamic Memory Networks for Dialogue Topic Tracking

Dialogue topic tracking aims at identifying the topic states in on-going multi-topic conversations. This paper proposes dynamic memory networks for dialogue topic tracking to learn the context states of conversations represented by multiple memory slots. The slot values are managed by the gated recurrent architectures with the update and reset gates considering cross-slot interactions. The experimental results show that our proposed models significantly improved both the sequential labelling and segmentation performances in topic tracking of human-human conversations in comparison to the other neural network baselines.
A Modern Greek online course designed through participatory design and social distributed constructionism

We present the implementation of Distributed Constructionism (DC) through a Participatory Design (PD) methodology for an Online Greek Language Learning community. Participatory design will be implemented as a four step process: (a) Build bridges with the intended users (b) Map user needs and suggestions to the system (c) Develop a prototype (d) Integrate feedback and continue the iteration. The success of this course was assessed through a series of evaluation exercises, result of which are presented here. Zaphiris P., Laghos A. , Zacharia G. (2005). A Modern Greek Online Course designed through Participatory Design and Social Distributed Constructionism. Themes in Education Journal, Special Issue: Information & Communication Technologies in Diaspora, 6 (1), pp 111-124
A Novel Real-Time Facial Expression Capturing Method

In this paper, we propose a new facial expression capturing method in real-time mode. Our proposed method main includes two processes: 1) Online process and 2) Offline process. The offline process adopt human face database to build 2D face model and 3D shape model, and then train an expression feature model. Afterwards, online process extracts feature points from human face images, and then obtains facial expression by SVM classifier which is trained from offline process. The main creativity of our method lies in that we propose an effective face detection approach and propose an optimal evaluation method to facial expression recognition. Experimental results show that our approach can capture facial expression precisely in real-time mode.
Adaptive waveform selection for tracking in clutter

Presents an adaptive waveform selective probabilistic data association (WSPDA) algorithm for tracking a single target in clutter. The assumption of an optimal receiver allows the inclusion of transmitted waveform specification parameters in the tracking subsystem equations, leading to a waveform selection scheme where the next transmitted waveform parameters are selected to minimise the total mean-square tracking error at the next time step. A simulation example demonstrates the potential of WSPDA tracking filters over conventional probabilistic data association (PDA) tracking filters.
Improving Shepherd's Length Composition Analysis (SLCA) method for growth parameter estimations

Shepherd's "weekly parametric" method for estimating the parameter L sub( infinity ) and K of the von Bertalanffy growth function from length-frequency data often fails to converge, and usually overestimates K. It is shown that this is due to overcounting of the frequencies associated with large, slow growing fish, and that both of these problems can be completely overcome by a simple change in the way the scoring function is formulated.