Miracle-dz/UniFAR-FTUs huggingface dataset:
Low Space Complexity  $GF(2^m)$  Multiplier for Trinomials Using  $n$ -Term Karatsuba Algorithm

We propose bit-parallel <inline-formula> <tex-math notation="LaTeX">$GF(2^{m})$ </tex-math></inline-formula> multipliers for irreducible trinomials using an <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula>-term Karatsuba algorithm and Mastrovito approach, which are generalizations of the newly proposed multiplication scheme for a specific trinomial. The complexities of the proposed multipliers for <inline-formula> <tex-math notation="LaTeX">$GF(2^{m})$ </tex-math></inline-formula> depend on the choice of an irreducible trinomial <inline-formula> <tex-math notation="LaTeX">$x^{m}+x^{k}+1$ </tex-math></inline-formula> defining <inline-formula> <tex-math notation="LaTeX">$GF(2^{m})$ </tex-math></inline-formula> and values <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$m_{0}$ </tex-math></inline-formula> such that <inline-formula> <tex-math notation="LaTeX">$m=nm_{0}$ </tex-math></inline-formula> or <inline-formula> <tex-math notation="LaTeX">$m=nm_{0}+1$ </tex-math></inline-formula>. It is possible to achieve a space-time tradeoff by choosing proper values for <inline-formula> <tex-math notation="LaTeX">$k,~n$ </tex-math></inline-formula>, and <inline-formula> <tex-math notation="LaTeX">$m_{0}$ </tex-math></inline-formula>. For the purpose of a specific comparison, we compare the proposed multipliers with the best-known multipliers for an odd <inline-formula> <tex-math notation="LaTeX">$m\in [{399,450}]$ </tex-math></inline-formula> for which there exists an irreducible trinomial of degree <inline-formula> <tex-math notation="LaTeX">$m$ </tex-math></inline-formula>. As a result, the proposed multipliers achieve the lowest space complexities among similar bit-parallel multipliers (they have roughly 40% reduced space complexities compared with the fastest multiplier). On the other hand, their time complexities match or are at most <inline-formula> <tex-math notation="LaTeX">$2T_{X}$ </tex-math></inline-formula> higher than the fastest multipliers, where <inline-formula> <tex-math notation="LaTeX">$T_{X}$ </tex-math></inline-formula> is the delay of one 2-input XOR gate.
Finding Impact Factors for Rejection of Pull Requests on GitHub

A pull request is an important method for code contributions in GitHub that will be submitted when the developers would like to merge their code changes from their local machine to the main repository on which all source code in the project are stored. Before merging the code changes into the main repository, the developers have to request for a permission. If their source code is allowed to merge, the pull request status is accepted. On the other hand, if their source code is not allowed to merge, the pull request status is rejected. The pull request status may be rejected due to several factors, such as code complexity, code quality, the number of changed files, etc. Fixing the rejected pull requests will take some extra effort and time which may affect the project cost and timeline. This paper aims at finding the impact factors that are associated with the rejection of pull requests on GitHub and also discovering the relationships among impact factors by using the association rules in data mining.
Enhanced Approach for Finger-Vein Extraction

Recently, recognition systems of finger vein have been used for personal identification. Finger vein is more promising than the existing biometric system in terms of security and convenience. However, accuracy may be reduced depending on the performance of the machine or the environment surrounding it. We propose an algorithm to improve recognition systems of finger vein. Extracted the finger vein apply the modified median filter and image expansion. The simulations used data from MMCBNU_6000 of Chungbuk National University and the performance were analyzed using the FAR, FRR, and EER.
The perceived effectiveness of the Restaurant Watch program in Vancouver, British Columbia

Gang violence in British Columbia poses a significant concern for law enforcement agencies and the public. In response to this violence, the Restaurant Watch program, a targeted enforcement strategy that deters unwanted gang-involved patrons from attending participating restaurants, was created and implemented in the city of Vancouver. The current study examined this program and its perceived effectiveness by key stakeholders. Data for this study was collected by conducting semi structured interviews with key stakeholders who enforce and participate in the program. The program’s objectives and operations were explored in the context of the gang landscape in British Columbia. Given that the Restaurant Watch program is unique, the author draws on the findings of other anti-gang deterrent projects, such as the Operation Ceasefire and the London’s Operation Shield, to explain and analyze the program’s objectives and methods. The findings suggest that the program is successful due to three important themes: (1) the impact on public safety; (2) the importance of partnership and open dialogue and; (3) the ability to deter inadmissible patrons from participating establishments.
Real-time environmental monitoring, visualization and notification system for construction H&S management

Construction workers who are exposed to hot and humid environments are at high risk of heat stress. Excessive exposure to such environments can result in occupational illnesses and injuries. Acquisition of sensor data from such environments is essential to ensure improved Health and Safety (H&S) of workers. Building Information Modeling (BIM) offers a new epitome to provide comprehensive solutions for H&S and evacuation planning in buildings. Researchers around the globe have presented hybrid solutions for integrating different sensing technologies with BIM such as Radio Frequency Identification (RFID) tags, Ultra High Frequency (UHF) readers and sensors. A review and critical evaluation of literature on integrated solutions of BIM with various sensing technologies is performed in order to present a hybrid solution based on BIM and Wireless Sensors Network (WSN) along with a notification system for real-time environmental monitoring of buildings. The application, entitled “Real-Time Environmental Monitoring, Visualization and Notification System”, is expected to provide a new horizon for effective visualization, reliable data capturing and catering to time sensitive emergency situations for construction H&S management. The paper will also outline scope of future research in this domain.
A review of building information modeling protocols, guides and standards for large construction clients

Large construction clients (companies, public authorities and government departments) perceive the need to facilitate and accelerate adoption of Building Information Modeling (BIM) for their projects because they derive significant benefits from its use for design, construction and operation of their facilities. Preparation of appropriate BIM guidelines that can be mandated through contracts is one of the main steps they can take to promote adoption. With a view to aiding such organizations to compile comprehensive guideline documents, we present a qualitative content analysis of fifteen BIM guideline, standard and protocol documents published to date, identifying both common features and missing aspects. While the main topics covered are similar across all the standards and guides – interoperability, collaboration modes, BIM execution plan, simulation & analysis, BIM manager’s role and operation & maintenance requirements – their content, specificity, frequency and level of resolution are different. The category and topic analysis led to derivation of a set of essential requirements. Recommendations are provided to help organizations/governments compile their own documents and establish policies compatible with their specific context and needs.
Implementing PSK and FSK Scheme in Zynq-7000 FPGA for SDR Applications

This paper presents a versatile approach to implement BPSK (Binary Phase Shift Keying), QPSK (Quadrature Phase Shift Keying), FSK (Frequency Shift Keying), QFSK (Quadrature Frequency Shift Keying), M-PSK (M-ary Phase Shift Keying) and M-FSK (M-ary Frequency Shift Keying) on a Zynq 7000 All Programmable SoC which can find application in SDR (Software Defined Radio). The designs are implemented using Verilog HDL (Hardware Description Language) and the tool used is Vivado IDE (Integrated Development Environment) 2017.4 by Xilinx. The system follows a modular approach to make the design easy to modify and reuse. The design approach followed is a top-down portraying the primary modules and then moving into details of each module implementation. The Sine wave is generated using a look-up-table and the phase or frequency values of the sine wave produced is dependent upon the modulating message bits. With symbol sample frequency selection input the design is able to switch the rate at which the input message symbols are sampled facilitating the design to switch between message symbol sampling rate on the fly. These features of the design can find potential applications in SDR (Software Defined Radio).
Long-range Hand Gesture Recognition with Joint SSD Network

The hand gesture recognition plays an important role in the human-computer interaction (HCI) field. Previous works mainly focused on researching this task in the shorter distance, which can only be applied in a limited scenario due to the recognition distance constrains. In this paper, we propose a method, which is named Joint Single Shot Multibox Detector (JSSD) network, to solve the hard long-distance hand gesture recognition task. The method is based on the framework of SSD. Our model employed two SSDs for object detection. One is for the head-shoulder region detection and the other is for the hand gesture bounding box proposal and classification. We validate our proposed model on real data collected from USB camera at several distance levels. The experiment results show that our method is more robust and precise in recognizing the hand gestures at a longer distance. Concretely, JSSD network is able to recognize the hand gestures captured up to 6 meters away from the camera.
Deep Learning Models for Cyber Security in IoT Networks

In this paper we propose deep learning models for the cyber security in IoT (Internet of Things) networks. IoT network is as a promising technology which connects the living and non-living things around the world. The implementation of IoT is growing fast but the cyber security is still a loophole, so it is susceptible to many cyber-attack and for the success of any network it most important that the network is completely secure, otherwise people could be reluctant to use this technology. DDoS (Distributed Denial of Service) attack has affected many IoT networks in recent past that has resulted in huge losses. We have proposed deep learning models and evaluated those using latest CICIDS2017 datasets for DDoS attack detection which has provided highest accuracy as 97.16% also proposed models are compared with machine learning algorithms. This paper also identifies open research challenges for usage of deep learning algorithm for IoT cyber security.
Comparison of the Aerodynamic Characteristics of the Eppler-197 and Modified Eppler-197 Airfoil Sections at Mach Number from 0.4 to 0.75

The objective of this paper is to study the aerodynamic characteristics of the modified Eppler-197 airfoil sections at high-subsonic Mach number. The mean-camber line of Eppler-197 airfoil section was used as the basic mean-camber line for the two modified airfoils. The surface around the mean-camber was created by using the symmetrical airfoil profiles, NACA64012 and NACA65012. The computational fluid dynamic code, ANSYS FLUENT, was used to determine the lift, drag, pitching-moment characteristics and drag-divergence Mach number of the modified airfoils. The flow condition in this study was at Reynolds number 3×106 and the Mach number varies from 0.4 to 0.75. The angle of attack was varied from the –2° to 6°. The results from calculation were compared with the data of the original Eppler-197 profile. The study shows that the modified profiles have better aerodynamic characteristics at all Mach number range. The lift-to-drag ratio of the modified profiles are higher than the original profile. The drag-divergence Mach number of modified airfoils increases between 0.69 percent to 7.15 percent at lift coefficient from 0.1 to 1.1. The rate of drag rise above the drag-divergence Mach number of the modified profiles are lower than the original profile. The pitching moment does not have significantly change.
RNA Interference in the Tobacco Hornworm, Manduca sexta, Using Plastid-Encoded Long Double-Stranded RNA

RNA interference (RNAi) is a promising method for controlling pest insects by silencing the expression of vital insect genes to interfere with development and physiology; however, certain insect Orders are resistant to this process. In this study, we set out to test the ability of in planta-expressed dsRNA synthesized within the plastids to silence gene expression in an insect recalcitrant to RNAi, the lepidopteran species, Manduca sexta (tobacco hornworm). Using the Manduca vacuolar-type H+ ATPase subunit A (v-ATPaseA) gene as the target, we first evaluated RNAi efficiency of two dsRNA products of different lengths by directly feeding the in vitro-synthesized dsRNAs to M. sexta larvae. We found that a long dsRNA of 2222 bp was the most effective in inducing lethality and silencing the v-ATPaseA gene, when delivered orally in a water droplet. We further transformed the plastid genome of the M. sexta host plant, Nicotiana tabacum, to produce this long dsRNA in its plastids and performed bioassays with M. sexta larvae on the transplastomic plants. In the tested insects, the plastid-derived dsRNA had no effect on larval survival and no statistically significant effect on expression of the v-ATPaseA gene was observed. Comparison of the absolute quantities of the dsRNA present in transplastomic leaf tissue for v-ATPaseA and a control gene, GFP, of a shorter size, revealed a lower concentration for the long dsRNA product compared to the short control product. We suggest that stability and length of the dsRNA may have influenced the quantities produced in the plastids, resulting in inefficient RNAi in the tested insects. Our results imply that many factors dictate the effectiveness of in planta RNAi, including a likely trade-off effect as increasing the dsRNA product length may be countered by a reduction in the amount of dsRNA produced and accumulated in the plastids.
Groove Explorer: An Intelligent Visual Interface for Drum Loop Library Navigation

Music producers nowadays rely on increasingly large libraries of loops, samples and virtual instrument sounds as part of the composition process. Intelligent interfaces are therefore useful in enabling navigation of these databases in a way that supports the production workflow. Within virtual drumming software, producers typically rely on large libraries of symbolic drum loops. Due to their large size, navigating and exploring these libraries can be a difficult process. To address this, preliminary work is presented into the Groove Explorer. Using Self-Organizing Maps, a large library of symbolic drum loops is automatically mapped on a 2D space according to rhythmic similarity. This space can then be explored via a Max/MSP prototype interface. Early results suggest that while the algorithm works well for smaller datasets, further development is required, particularly in the similarity metric used, to make the tool scalable to large libraries.
The perceived value of building information modeling in the U.S. building industry

Although measuring the business value of BIM has attracted the attention of practitioners and researchers, there has been a lack of consistent cost-benefit benchmarking associated with BIM process enhancements and innovations. An increase in the availability of cost-benefit information will be significant, as one of the primary motivators for professionals in the building industry to adopt new technologies is the opportunity for direct benefits in their own operations. This paper presents findings from an industry-wide online survey that was carried out in the spring of 2009. The study aims to understand the perceived value of BIM in the U.S. building industry, as seen by various participants in the industry. The survey specifically focuses on tangible benefits and costs associated with BIM use at the project level.
Improving collaboration between engineering and construction in detail engineering using a project execution model and BIM

The construction industry is under pressure to reduce project delivery time and costs despite increased project complexity. A challenge is that engineering and construction are not well integrated. Usually engineering takes place during a given period, followed by construction. Demands for shorter delivery time, indicate that construction should be pushed in parallel with engineering, with better correlation between how one conducts engineering and plan to build. To address this, the construction industry would benefit from gathering knowledge and learn from other relevant industries. How can collaboration and transition between engineering and construction in detail engineering be improved, with the use of a project execution model and utilization of BIM? Research is based on case studies of major oil and gas projects. Data is collected through an EPC (engineering, procurement and construction) contractor and two engineering contractors. The projects have been executed as EPC contracts (design-build), where engineering and procurement is subcontracted. The paper assess how collaboration between engineering and construction can be improved with a combination of aspects related to process, people and technology. The first, process, is how parallelism between engineering and construction is based on frozen design, and how engineering can adapt to a construction sequence, by adjusting milestone requirements and deliver “right the first time”. The second, people, is how relational contracts, with focus on relationship and common goals, can be used and how engineering teams can be selected and developed to support this. The third, technology, is how engineering can split building information models, to support fabrication.
A Varied Density-based Clustering Approach for Event Detection from Heterogeneous Twitter Data

Extracting the latent knowledge from Twitter by applying spatial clustering on geotagged tweets provides the ability to discover events and their locations. DBSCAN (density-based spatial clustering of applications with noise), which has been widely used to retrieve events from geotagged tweets, cannot efficiently detect clusters when there is significant spatial heterogeneity in the dataset, as it is the case for Twitter data where the distribution of users, as well as the intensity of publishing tweets, varies over the study areas. This study proposes VDCT (Varied Density-based spatial Clustering for Twitter data) algorithm that extracts clusters from geotagged tweets by considering spatial heterogeneity. The algorithm employs exponential spline interpolation to determine different search radiuses for cluster detection. Moreover, in addition to spatial proximity, textual similarities among tweets are also taken into account by the algorithm. In order to examine the efficiency of the algorithm, geotagged tweets collected during a hurricane in the United States were used for event detection. The output clusters of VDCT have been compared to those of DBSCAN. Visual and quantitative comparison of the results proved the feasibility of the proposed method.
Predicting Adolescent Depression: The Interrelated Roles of Self-Esteem and Interpersonal Stressors

Depression in adolescents can lead to social and educational impairment and is a major risk factor for suicide and substance misuse. Thus, predicting and preventing this disorder are extremely important. The current study aimed to analyze the contribution of adolescents’ self-esteem (i.e., quality of interpersonal relationships, control of life events, and management of negative emotions) and interpersonal stressor sources (relationships with parents, teachers, classmates and friends) in predicting several depression manifestations (i.e., depressed mood, sense of inadequacy, and insecurity). Participants were 182 Italian pre-adolescents and adolescents, aged 10–14 years, were recruited from three Italian schools. They were asked to complete a self-report questionnaire. Results showed that self-esteem was a major factor to be considered in adolescents’ depression. In particular, adolescents’ perception of negative emotion management was the most important protective factor against depression manifestations. Conversely, sources of interpersonal stressors contributed only marginally to depression. Among these, problems with parents and friends increased adolescents’ depressed mood, while troubles with classmates impacted on their sense of inadequacy and insecurity. Implications of these results for positive practices which could enhance adolescents’ self-esteem and further expansions of the study are discussed.
Characterization of Subtilin L-Q11, a Novel Class I Bacteriocin Synthesized by Bacillus subtilis L-Q11 Isolated From Orchard Soil

Bacteriocins are peptides or proteins synthesized by bacterial ribosomes that show killing or inhibitory activities against different groups of bacteria. Bacteriocins are considered potential alternatives to traditional antibiotics, preservatives in pharmaceutical and food industries. A strain L-Q11 isolated from orchard soil was phylogenetically characterized as Bacillus subtilis based on 16S rRNA gene sequencing analysis. A novel class I bacteriocin (Subtilin L-Q11), was identified and purified from L-Q11 cell-free supernatant in a four-step procedure, including salt precipitation, cation exchange, gel filtration, and reverse-phase high-performance liquid chromatography (RP-HPLC). The molecular mass (3,552.9 Da) of this novel bacteriocin was determined by Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). The purified Subtilin L-Q11 exhibited optimal features in pH tolerance, thermostability, and sensitivity to proteases. Further, Subtilin L-Q11 showed inhibitory activities against a number of bacteria including some human pathogens and food spoilage bacteria, in particular Staphylococcus aureus. All these important features make this novel bacteriocin a potential candidate for the development of a new antibacterial drug or food preservative in the future.