Miracle-dz/UniFAR-FTUs huggingface dataset:
Assigning Library of Congress Classification Codes to Books Based Only on their Titles

Many publishers follow the Library of Congress Classification (LCC) scheme to indicate a classification code on the first pages of their books. This is useful for many libraries worldwide because it makes possible to search and retrieve books by content type, and this scheme has become a de facto standard. However, not every book has been pre-classified by the publisher; in particular, in many universities, new dissertations have to be classified manually. Although there are many systems available for automatic text classification, all of them use extensive information which is not always available, such as the index, abstract, or even the whole content of the work. In this work, we present our experimentson supervised classification of books by using only their title, which would allow massive automatic indexing. We propose a new text comparison measure, which mixes two well-known text classification techniques: the Lesk voting scheme and the Term Frequency (TF). In addition, we experiment withdifferent weighing as well as logical-combinatorial methods such as ALVOT in order to determine the contribution of the title in the correct classification. We found this contribution to be approximately one third, as we correctly classified 36% (on average by each branch) of 122,431 previously unseen titles (in total) upon training with 489,726 samples (in total) of one major branch (Q) of the LCC catalogue.Povzetek: Opisan je postopek klasifikacije knjig na osnovi naslovov v ameriski kongresni knjižnici.
Fault Tolerant Flight Control, a Physical Model Approach

Safety is of paramount importance in all transportation systems, but especially in civil aviation. Therefore, in civil aviation, a lot of developments focus on the improvement of safety levels and reducing the risks that critical failures occur. When one analyses recent aircraft accident statistics, it is clear that a significant portion is attributed to “loss of control in flight”. A recent worldwide civil aviation accident survey for the 1989 to 2003 period, conducted by the Civil Aviation Authority of the Netherlands (CAA-NL) and based on data from the National Aerospace Laboratory NLR, indicates that this category accounts for as much as 17% of all aircraft accident cases. This has led to a common conclusion: from a flight dynamics point of view, with the technology and computing power available on this moment, it might have been possible to recover a part of the aircraft in the accident category described above on the condition that non-conventional control strategies would have been applied. These non-conventional control strategies involve the so-called concept of fault tolerant flight control (FTFC), where the control system is capable to detect and adapt for changes in the aircraft behaviour. One FTFC strategy option is using a model based control routine. This research focuses on a physical modular approach. In this setup, not only a reconfiguring controller is needed, but also a suitable FDI/identification strategy. This research focuses on both components. In this reseach project, a real-time aerodynamic model identification procedure has been combined with a model based adaptive control method. A manual as well as an autopilot version have been developed. The autopilot version has been evaluated on desktop simulations, the manual version has been tested in the Simona Research Simulator involving professional airline pilots. Both tests have demonstrated promising results. The autopilot performance is very good, and the manual controller has demonstrated to increase handling qualities and to reduce pilot workload of the damaged aircraft. These are very promising results that motivate further research in this field.
Head and Neck Metastatic Tumors: a Retrospective Survey of Iranian Patients

Statement of the Problem The head and neck region is an uncommon site for metastatic involvement, but it can be the first and only symptom of primary cancer. The incidence of these tumors and their primary origins are limited in Iranian patients. Purpose Therefore, this retrospective study aimed to investigate the frequency and the common related clinical manifestations, as well as, the most common types of cancers and the prevalent sites of the primary tumor. Materials and Method All medical records related to patients with history of head and neck tumors between 1991 and 2011 at Iran Cancer Institute were evaluated and the essential information was statistically analyzed. Results Sixty cases of cervical lymph node metastasis (0.36%) and 26 cases of head and neck metastatic tumors (0.16%) including 17 cases of distant cancer (0.10%) were recorded among all 16232 registered cancers. Out of all distant head and neck metastatic tumors, 4 cases were related to oral and maxillofacial area. Pain, swelling of neck, oral mucosa ulcer and dryness were the chief complaints. Squamous cell carcinoma and adenocarcinoma were the most frequent types of cancers. The most common metastatic sites were cervical musculature, scalp and parotid gland, and the most prevalent sites of primary tumor in females were breast and lung in males. Conclusion According to these cases, the incidence rate of head and neck metastatic tumors seems to be low. However, feasible similarity of clinical presentation of oral metastatic lesions to benign lesions might result in misdiagnosis. Hence, biopsy is mandatory in any case with unusual clinical presentation, especially in patients with a known malignant disease.
Cultural transmission results in convergence towards colour term universals

As in biological evolution, multiple forces are involved in cultural evolution. One force is analogous to selection, and acts on differences in the fitness of aspects of culture by influencing who people choose to learn from. Another force is analogous to mutation, and influences how culture changes over time owing to errors in learning and the effects of cognitive biases. Which of these forces need to be appealed to in explaining any particular aspect of human cultures is an open question. We present a study that explores this question empirically, examining the role that the cognitive biases that influence cultural transmission might play in universals of colour naming. In a large-scale laboratory experiment, participants were shown labelled examples from novel artificial systems of colour terms and were asked to classify other colours on the basis of those examples. The responses of each participant were used to generate the examples seen by subsequent participants. By simulating cultural transmission in the laboratory, we were able to isolate a single evolutionary force—the effects of cognitive biases, analogous to mutation—and examine its consequences. Our results show that this process produces convergence towards systems of colour terms similar to those seen across human languages, providing support for the conclusion that the effects of cognitive biases, brought out through cultural transmission, can account for universals in colour naming.
Path Selection Metrics for Performance-Improved Onion Routing

Providing anonymity for users on the Internet is a very challenging and difficult task. Currently there are only a few systems that are of practical relevance for the provision of low-latency anonymity. One of the most important to mention is Tor which is based on onion routing. Practical client usage of Tor often leads to delays that are not tolerated by the average end-user, which, in return, discourages many of them from using the system. In this paper we propose new methods of path selection that allow performance-improved onion routing. These are based on actively measured latencies and estimations of available link-wise capacities using passive observations of throughput. We evaluate the proposed methods in the public Tor network and present a practical approach to empirically analyze the strength of anonymity certain methods of path selection provide in comparison to each other.
Extracting Region of Interest (ROI) Details Using LBS Infrastructure and Web-Databases

The geographical areas that are considered to be popular and interesting are called Region of Interest (ROI). There are multiple sources that can be used for erecting the ROIs such as user trajectory, POI databases, internet news etc. A tourist spot, historical region, monuments, a forest reserve, city, state or country's administrative boundaries are considered as the ROI objects. The interesting facts of the regions can be used for on-the-spot infotainment (information + entertainment) while user is walking, driving or just sitting idle on the flight. One may want the information in different level of details based on the interests, travel direction, and speed. The best way to get the recent information is going through the internet news, discussion forums, and encyclopedias on the web. The challenge is that there is no universal database available that contains the region information along with the location based search capabilities. The maintaining the granularity of the information based on the size or the details of the region adds more challenges. The broader idea of our work is to use the existing LBS infrastructure to track the user and achieve other navigation objectives in the system. However, the freely available up-to-date internet infrastructure is used as the information source. Initially, the user location is determined by the conventional methods. In order to relate the location with the web content, we use the semantic labels associated to the underlying location. The semantic labels are fetched by using reverse geocoding that returns the local attractions, street city, state and country names etc. Then these labels are used to search the associated detailed content in the web. The region data is maintained in two forms i.e. locally populated database and the web databases. The locally populated database can be updated on the preconfigured time interval in order to avoid data staleness problem. We have used Wikipedia as the internet data source in our prototype. The further research is in progress extracting the ROI information from the POI databases with their spatial and non-spatial attributes.
Describe how comprehensive improvement services that result in dramatic, documented and sustainable improvement in underperforming urban secondary schools will be delivered to LEA’s that contract for your services. Comprehensive services include, but are not limited to the following: Support systems

nstructions: Section B responses must be in narrative form. Provide data/documentation of previous achievements where applicable. All responses must comply with stated page limits. Figures such as tables, charts and graphs can be included in the narrative, but such information will be counted toward page limits. Text and figures beyond the stated page limit will not be considered and should not be submitted with the application. All references must be cited.
WIDER Working Paper No . 2013 / 004 Aid as a catalyst for pioneer investment

I discuss how aid can support growth in small, isolated economies. Small markets frustrate scale economies and competition. Combined with high transport costs, essential inputs become prohibitively expensive. Breaking the coordination problem requires pioneering investment. Since this generates externalities it will be undersupplied. Donors have both the finance and the long-term relationships that could offset the externalities and political risks that impede pioneers. However, there are practical difficulties of how such support is best organized. In order of ambition these run from finance of infrastructure, through subsidized capital and political risk insurance, to long-term partnerships with private firms.
Array codes for clustered column erasures

A new error model is proposed for codes over channels with memory. According to this error model, both the number of symbol errors and the number of error clusters are used to characterize permissible errors. Considering this model as a generalization of random erasures in array codes naturally captures the properties of high-order failure events in disk arrays. A new family of codes tailored to such a model is shown to provide significant complexity improvements compared to known array codes.
Follow Us on Twitter at Http://twitter.com/blogcacm from Michael Stonebraker's " the Nosql Discussion Has Nothing to Do with Sql "

The Communications Web site, http://cacm.acm. org, features more than a dozen bloggers in the BLOG@CACM community. In each issue of Communications, we'll publish excerpts from selected posts. Recently, there has been a lot of buzz about NoSQL databases. In fact, there were at least two conferences on the topic in 2009, one on each coast. Seemingly , this buzz comes from people who are proponents of: document-style stores in which a database record consists of a collection of key-value pairs plus a payload. Examples of this class of system include CouchDB and MongoDB, and we call such systems document stores for simplicity; key-value stores whose records consist of key-payload pairs. Usually, these are implemented by distributed hash tables, and we call these key-value stores for simplicity. Examples include MemcacheDB and Dynamo. In either case, one usually gets a low-level, record-at-a-time database management system (DBMS) interface instead of SQL. Hence, this NoSQL databases are most often considered: update-and lookup-intensive online transaction processing (OLTP) workloads, not query-intensive, data-warehousing workloads. We do not consider document repositories or other specialized workloads for which NoSQL systems may be well suited. There are two ways to improve OLTP performance; namely, provide automatic sharding over a shared-nothing processing environment and improve per-server OLTP performance. In the first case, one improves performance by providing scalability as nodes are added to a computing environment ; in the second case, one improves the performance of individual nodes. Every serious SQL DBMS—such as Greenplum, Aster Data, Vertica, ParAccel, and others—written in the last 10 years has provided shared nothing scalability, and any new effort would be remiss if it did not do likewise. Hence, this component of performance should be " table stakes " for any DBMS. In my opinion, nobody should ever run a DBMS that does not provide automatic sharding over computing nodes. As a result, this posting continues about the other component; namely, single-node OLTP performance. The overhead associated with OLTP databases in traditional SQL systems has little to do with SQL, which is why " NoSQL " is such a misnomer. Instead, the major overhead in an OLTP SQL DBMS is communicating with the DBMS using ODBC or group identifies itself as advocating NoSQL. There are two possible reasons to move to either of these alternate DBMS technologies: performance and flexibility. The performance argument goes something like the following: I started with MySQL for my data storage needs …
High-Order Measurements for Residual Classifiers

Residual classifiers are common in dictionary-based multiclass classification. This paper proposes the concept of performance functions for residual classifiers. A performance function for multiclass classifications is a conceptual measurement function that combines local and global measurements. In general, the performance function is nonlinear. To explore the properties of the performance function, we employ the Taylor series expansion technique and derive a family of measurement functions. Specifically, the linear measurement and the quadratic measurement (QM) are derived. By exploiting the effect of the higher order terms in the performance function as well as the fundamental nondecreasing constrain, we derive the normalized QM (NQM). We present the classifier for multiclass classification using the proposed measurements. The proposed algorithms are tested against frontal faces and handwritten digit recognition tasks. Our tests show that the QM classifier achieves competitive classification results compared with baseline methods. NQM shows better stability with different parameter configurations.
Empirical Investigation of Code and Process Metrics for Defect Prediction

Data science is becoming more important for software engineering problems. Software defect prediction is a critical area which can help the development team allocate test resource efficiently and better understand the root cause of defects. Furthermore, it can help find the reason why a component or even a project is failure-prone. This paper deals with binary classification in predicting if a software component has a bug by using three widely used machine learning algorithms: Random Forest (RF), Neural Networks (NN), and Support Vector Machine (SVM). The paper investigates the applications of these algorithms to the challenging issue of predicting defects in software components. This paper combines code metrics and process metrics as indicators for the Eclipse environment using the aforementioned three algorithms for a sample of weekly Eclipse features. Feature reduction is also adopted using General Linear Model (GLM) to save computational time. The results confirm the predictive capabilities of using two features -- NBD_max and Pre-defects -- and are comparable to the results of using all 61 features. Additionally, this paper evaluates the performance of the three algorithms. NN and RF turn out to have the best fit.
Human Polyomavirus Reactivation: Disease Pathogenesis and Treatment Approaches

JC and BK polyomaviruses were discovered over 40 years ago and have become increasingly prevalent causes of morbidity and mortality in a variety of distinct, immunocompromised patient cohorts. The recent discoveries of eight new members of the Polyomaviridae family that are capable of infecting humans suggest that there are more to be discovered and raise the possibility that they may play a more significant role in human disease than previously understood. In spite of this, there remains a dearth of specific therapeutic options for human polyomavirus infections and an incomplete understanding of the relationship between the virus and the host immune system. This review summarises the human polyomaviruses with particular emphasis on pathogenesis in those directly implicated in disease aetiology and the therapeutic options available for treatment in the immunocompromised host.
P-ZnO/n-Si Photodiodes Prepared by Ultrasonic Spraying Pyrolysis Method

ZnO ultraviolet (UV)/visible photodiodes were fabricated. The N-In codoped p-type ZnO films were deposited on (111)-oriented silicon substrate by ultrasonic spraying pyrolysis method. It was found the photocurrent approximately 3.9� 10 -7 A at a bias of 1 V and a photocurrent to dark current contrast ratio higher than around two orders of magnitude. The photodiodes exhibited two higher responsive regions denoted as A and B, respectively. Region A at wavelength from 400 nm to 700 nm was owing to ZnO film absorption occurring through the band-to-deep level, and region B at wave- length from 700 nm to 1000 nm was owing to Si substrate absorption occurring through the band edge.
SensorFall - An Accelerometer Based Mobile Application

In recent years, the use of sensors in mobile devices is extremely desirable. In particular, an accelerometer can be used for numerous applications such as tracking objects or monitoring elderly people. This paper presents an application tool based on an accelerometer, called SensorFall, to detect and notify the acceleration caused by a fall. We have implemented and verified the SensorFall in several environments, such as in a hospital or in a regular daily life, for older people. The obtained results show that it performs well.
Synthetic Observations of the HI Line in SPH-Simulated Spiral Galaxies

Using the radiative transfer code Torus, we produce spectral-line cubes of the predicted HI profile from global SPH simulations of spiral galaxies. Torus grids the SPH galaxy using Adaptive Mesh Refinement, then applies a ray-tracing method to infer the HI profile along the line(s) of sight. The gridded galaxy can be observed from any direction, which enables us to model the observed HI profile for galaxies of any orientation. We can also place the observer inside the galaxy, to simulate HI observations taken from the Earth's position in the Milky Way.
Procrastination and Self-Efficacy Among Intravenous Drug Users on a Methadone Maintenance Program in Sari City, Iran, 2013

Background: Self-efficacy is the belief that one has the ability to implement the behaviors needed to produce a desired effect. There has been growing interest in the role of self-efficacy as a predictor and/or mediator of treatment outcome in a number of domains. Procrastination is a self-regulatory failure, defined as the voluntary delay of an intended course of action despite expecting to be worse off for the delay. Behavioral procrastination is a self-sabotage strategy that allows people to shift blame and avoid action; the decisional procrastination strategy is to put off making a decision when dealing with conflicts or choices. Procrastination has a great role in quitting drug addiction. Objectives: The aim of this study was to determine the relationship between procrastination and self-efficacy and other factors among intravenous drug users. Patients and Methods: This cross-sectional study was conducted on 178 intravenous drug users in the behavioral disease counseling, health center in Sari city, Mazandaran province, Iran, in 2013. The samples were selected through census sampling, descriptive and inferential statistics were used to measure the properties of distribution that depicts a set of data shown as frequency distribution tables, while for the mean and standard deviation, chi-square, Fisher and Spearman-Brown coefficients were used to analyze the data. Results: The mean age of the participants was 43 years. Seventy-two percent of them were married and opium was the first drug used. The first substance used in them was 54% of opium, 33% cannabis and 5% alcohol and 79% smoking. The reason of the first drug use in 32% of the subjects was temptation and in 10% a friend’s influence. The mean age of the first drug use was 23 years, and the frequency was 2 times per day. All of them had relapse at least once. Seven percent of them currently use other materials (2% crystal, 5% alcohol and opium and crack) both in methadone treatment. Behavioral procrastination in 60.5% of them and decisional procrastination in 62% is from low to average range. There was a significant relationship between relapse and self-efficacy as well as between self-efficacy and the age of the first drug use, drug dose, and procrastination for treatment, marriage, employment and job. Also, the relationship between behavioral procrastination and self-efficacy was significant and inverse. Conclusions: This study found a significant difference between procrastination and self-efficacy as well as other related factors. It is important to include drug users and the society organizations representing them in every stage of the governmental policy and program development process to make them responsive to the needs of the community.