snu-aidas/HVMap-dataset huggingface dataset:
Mid-level deep pattern mining

Mid-level visual element discovery aims to find clusters of image patches that are both representative and discriminative. In this work, we study this problem from the prospective of pattern mining while relying on the recently popularized Convolutional Neural Networks (CNNs). Specifically, we find that for an image patch, activation extracted from the first fully-connected layer of a CNN have two appealing properties which enable its seamless integration with pattern mining. Patterns are then discovered from a large number of CNN activations of image patches through the well-known association rule mining. When we retrieve and visualize image patches with the same pattern (See Fig. 1), surprisingly, they are not only visually similar but also semantically consistent. We apply our approach to scene and object classification tasks, and demonstrate that our approach outperforms all previous works on mid-level visual element discovery by a sizeable margin with far fewer elements being used. Our approach also outperforms or matches recent works using CNN for these tasks. Source code of the complete system is available online.
Does Computer-Assisted Learning Improve Learning Outcomes ? Evidence from a Randomized Experiment in Migrant Schools in Beijing

The	  education	  of	  the	  poor	  and	  disadvantaged	  population	  has	  been	  a	  long-­‐standing challenge	  to	  the	  education	  system	  in	  both	  developed	  and	  developing	  countries. Although	  computer-­‐assisted	  learning	  (CAL)	  has	  been	  considered	  one	  alternative	  to improve	  learning	  outcomes	  in	  a	  cost-­‐effective	  way,	  the	  empirical	  evidence	  of	  its	  impacts on	  improving	  learning	  outcomes	  is	  mixed.	  This	  paper	  intends	  to	  explore	  the	  nature	  of the	  effects	  of	  CAL	  on	  student	  academic	  and	  non-­‐academic	  outcomes	  for	  underserved populations	  in	  a	  developing	  country.	  To	  meet	  this	  goal,	  we	  exploit	  a	  randomized	  field experiment	  of	  a	  CAL	  program	  involving	  over	  4000	  third-­‐grade	  students,	  mostly	  from poor	  migrant	  families,	  in	  43	  migrant	  schools	  in	  Beijing.	  The	  main	  intervention	  is	  a	  math CAL	  program	  that	  is	  held	  out	  of	  regular	  school	  hours.	  The	  program	  is	  tailored	  to	  the regular	  school	  math	  curriculum	  and	  is	  remedial	  in	  nature.	  Our	  results	  show	  that,	  the	  CAL program	  improved	  the	  student	  standardized	  math	  scores	  by	  0.14	  standard	  deviations and	  most	  of	  the	  program	  effect	  took	  place	  within	  two	  months	  after	  the	  start	  of	  the program.	  Low-­‐performing	  students	  and	  those	  with	  less-­‐educated	  parents	  benefited more	  from	  the	  program.	  Moreover,	  CAL	  also	  significantly	  increased	  the	  levels	  of	  self-­‐ efficacy	  of	  the	  students	  and	  their	  interest	  in	  learning.	  We	  observed	  at	  most	  a	  moderate program	  spillover	  in	  Chinese	  test	  scores.	  Our	  findings	  are	  robust	  to	  the	  Hawthorne effect	  and	  CAL	  program	  spillovers	  that	  might	  potentially	  bias	  the	  estimates	  of	  the program	  effects. Key	  Words:	  	  Education;	  Development;	  Computer	  Assisted	  Learning;	  Random Assignment;	  Test	  Scores;	  China;	  Migration JEL	  Codes:	  I20;	  I21;	  I28;	  O15
Swarm-Based Spatial Sorting

Purpose – To present an algorithm for spatially sorting objects into an annular structure. Design/Methodology/Approach – A swarm-based model that requires only stochastic agent behaviour coupled with a pheromone-inspired “attraction-repulsion” mechanism. Findings – The algorithm consistently generates high-quality annular structures, and is particularly powerful in situations where the initial configuration of objects is similar to those observed in nature. Research limitations/implications – Experimental evidence supports previous theoretical arguments about the nature and mechanism of spatial sorting by insects. Practical implications – The algorithm may find applications in distributed robotics. Originality/value – The model offers a powerful minimal algorithmic framework, and also sheds further light on the nature of attraction-repulsion algorithms and underlying natural processes.
DeepID3: Face Recognition with Very Deep Neural Networks

The state-of-the-art of face recognition has been significantly advanced by the emergence of deep learning. Very deep neural networks recently achieved great success on general object recognition because of their superb learning capacity. This motivates us to investigate their effectiveness on face recognition. This paper proposes two very deep neural network architectures, referred to as DeepID3, for face recognition. These two architectures are rebuilt from stacked convolution and inception layers proposed in VGG net [10] and GoogLeNet [16] to make them suitable to face recognition. Joint face identification-verification supervisory signals are added to both intermediate and final feature extraction layers during training. An ensemble of the proposed two architectures achieves 99.53% LFW face verification accuracy and 96.0% LFW rank-1 face identification accuracy, respectively. A further discussion of LFW face verification result is given in the end.
FLEXIBLE MANUFACTURING SYSTEMS MODELLING AND PERFORMANCE EVALUATION USING AUTOMOD

In recent times flexible manufacturing systems emerged as a powerful technology to meet the continuous changing customer demands. Increase in the performance of flexible manufacturing systems is expected as a result of integration of the shop floor activities such as machine and vehicle scheduling. The authors made an attempt to integrate machine and vehicle scheduling with an objective to minimize the makespan using Automod. Automod is a discrete event simulation package used to model and simulate a wide variety of issues in automated manufacturing systems. The key issues related to the design and operation of automated guided vehicles such as flow path layout, number of vehicles and traffic control problems are considered in the study. The performance measures like throughput, machine and vehicle utilization are studied for different job dispatching and vehicle assignment rules in different flexible manufacturing system configurations. (Received in August 2010, accepted in April 2011. This paper was with the authors 1 month for 2 revisions.)
Digital Material Fabrication Using Mask-Image-Projection-based Stereolithography

Purpose – The purpose of this paper is to present a mask-image-projection-based Stereolithography process that can combine two base materials with various concentrations and structures to produce a solid object with desired material characteristics. Stereolithography is an additive manufacturing process in which liquid photopolymer resin is cross-linked and converted to solid. The fabrication of digital material requires frequent resin changes during the building process. The process presented in this paper attempts to address the related challenges in achieving such fabrication capability. Design/methodology/approach – A two-channel system design is presented for the multi-material mask-imageprojection-based Stereolithography process. In such a design, a coated thick film and linear motions in two axes are used to reduce the separation force of a cured layer. The material cleaning approach to thoroughly remove resin residue on built surfaces is presented for the developed process. Based on a developed testbed, experimental studies were conducted to verify the effectiveness of the presented process on digital material fabrication. Findings – The proposed two-channel system can reduce the separation force of a cured layer by an order of magnitude in the bottom-up projection system. The developed two-stage cleaning approach can effectively remove resin residue on built surfaces. Several multi-material designs have been fabricated to highlight the capability of the developed multi-material mask-image-projection-based Stereolithography process. Research limitations/implications – A proof-of-concept testbed has been developed. Its building speed and accuracy can be further improved. Our tests were limited to the same type of liquid resins. In addition, the removal of trapped air is a challenge in the presented process. Originality/value – This paper presents a novel and a pioneering approach towards digital material fabrication based on the Stereolithography process. This research contributes to the additive manufacturing development by significantly expanding the selection of base materials in fabricating solid objects with desired material characteristics.
Manufacturing Problem Solving in a Job Shop — Research in Layout Planning

For ensuring efficient operation of a job shop, it is important to minimize waste, which has no value addition to the final product. For a job shop, minimizing movement is considered as the highest priority for waste prevention. For this reason, the layout for a job shop should be designed in such a way to ensure the lowest possible cost for production by reducing nonvalue added activities, such as movement of work-in-process. An effective and efficient way of layout planning for a job shop is a key for solving movement inefficiencies and facilitating communication and interaction between workers and supervisors. This involves relocation of equipment and machinery to streamline materials flow. The primary objective of relocation is to avoid flow conflicts, reduce process time, and increase efficiency of labor usage. Proximity of the most frequently used machines minimizes the movement cost significantly, which eventually minimizes the cost of production. This paper describes the research done in process flow improvements in a job shop manufacturing steel components. The literature focused mainly on mathematical modeling with assumptions that are not applicable for a typical small-scale job shop operation. However, this was overcome by collecting material movement data over three months and analyzing the information using a From-To chart. By analyzing the chart, the actual loads between departments for the operation period were tabulated in available plant space. From this information, the inter-departmental flow was shown by a model. This provides the basic layout pattern, which was improved. A second step was to determine the cost of this layout by multiplying the material handling cost by the number of loads moved between each pair of departments. As a recommendation for solving the problem, two layout models have been developed for ensuring the lowest movement cost. Introduction Transportation is considered as one of the seven wastes for lean manufacturing, and effective layout planning is considered as a key to overcome this kind of waste. It is stated, “Double handling and excessive movements are likely to cause damage and deterioration with the distance of communication between processes” [1]. Therefore, layout planning has clear impact with the quality and quantity of the final products by reducing waste and improving efficiency.
Internet of Things Business Models

Almost all businesses are aware of the potential gains that the Internet of Things (IoT) has to offer, they are unsure of how to approach it. This article proposes a business model that builds on Holler et al., (2014) [1]. The model consists of three dimensions: “Who, Where, and Why”. “Who” describes collaborating partners, which builds the “Value Network”. “Where” describes sources of value co-creation rooted in the layer model of digitized objects, and “Why” describes how partners benefit from collaborating within the value network. With the intention of addressing “How”, the proposed framework has integrated the IoT strategy category, tactics, and value chain elements. The framework is then validated through the case studies of some successful players who are either the Awardees of the IoT Award 2014 or the ICT Award 2015 of Hong Kong.
Polymer Nanoparticles for Smart Drug Delivery

In the recent decades, polymers are widely used as biomaterials due to their favorable properties such as good biocompatibility, easy design and preparation, a variety of structures and interesting bio-mimetic character. Especially in the field of smart drug delivery, polymer played a significant role because it can deliver therapeutic agents directly into the intended site of action, with superior efficacy. The ideal requirements for designing nano-particulate delivery system are to effectively be controlled particle size, surface character; enhance permeation, flexibility, solubility and release of therapeutically active agents in order to attain the target and specific activity at a predetermined rate and time. The smart drug delivery systems have been successfully made by the advances in polymer science in the bio-nano‐ technology field. Recently, these advances have been found in various medical applications for nano-scale structures in smart drug delivery. The smart drug delivery systems should possess some important feature such as pre-scheduled rate, self controlled, targeted, predetermined time and monitor the delivery. The smart drug delivery system enhances the polymer nanoparticle better stage to their therapy regimen. They are drug carriers of natural, semi-synthetic, and synthetic polymeric nature at the nano-scale to micro-scale range. The polymeric particles are collectively named as spheres and capsules. The most of the polymeric nanoparticles with surfactants offer stability of various forms of active drugs and have useful to smart release properties. There are numerous biological applications have been reported for the nano-scale to micro-scale sized particles, such as site-targeted, controlled, and enhanced bioavailability of hydrophobic drugs [1-4]. Due to the nanoparticles size the drugs have been targeting into various applications, such as, various cancers targeting has been shown to be promising [5]. Moreover, polymeric particles proved their effectiveness in stabilizing and protecting the drug molecules such as proteins, peptides, or DNA molecules from various environmental hazards degradation [2-4, 6, 7]. So these polymers are affording the potential for various protein and gene delivery. Numerous methods had been available to fabricate
Gaussian quantum-behaved particle swarm optimization approaches for constrained engineering design problems

Particle swarm optimization (PSO) is a population-based swarm intelligence algorithm that shares many similarities with evolutionary computation techniques. However, the PSO is driven by the simulation of a social psychological metaphor motivated by collective behaviors of bird and other social organisms instead of the survival of the fittest individual. Inspired by the classical PSO method and quantum mechanics theories, this work presents novel quantum-behaved PSO (QPSO) approaches using mutation operator with Gaussian probability distribution. The application of Gaussian mutation operator instead of random sequences in QPSO is a powerful strategy to improve the QPSO performance in preventing premature convergence to local optima. In this paper, new combinations of QPSO and Gaussian probability distribution are employed in well-studied continuous optimization problems of engineering design. Two case studies are described and evaluated in this work. Our results indicate that Gaussian QPSO approaches handle such problems efficiently in terms of precision and convergence and, in most cases, they outperform the results presented in the literature. 2009 Elsevier Ltd. All rights reserved.
Double hierarchy hesitant fuzzy linguistic term set and MULTIMOORA method: A case of study to evaluate the implementation status of haze controlling measures

In recent years, hesitant fuzzy linguistic term sets (HFLTSs) have been studied by many scholars and are becoming gradually mature. However, some shortcomings of HFLTS also emerged. To describe the complex linguistic terms or linguistic term sets more accurately and reasonably, in this paper, we introduce the novel concepts named double hierarchy linguistic term set (DHLTS) and double hierarchy hesitant fuzzy linguistic term set (DHHFLTS). The operational laws and properties of the DHHFLTSs are developed as well. Afterwards, we investigate the multiple criteria decision making model with double hierarchy hesitant fuzzy linguistic information. We develop a double hierarchy hesitant fuzzy linguistic MULTIMOORA (DHHFL-MULTIMOORA) method to solve it. Furthermore, we apply the DHHFL-MULTIMOORA method to deal with a practical case about selecting the optimal city in China by evaluating the implementation status of haze controlling measures. Some comparisons between the DHHFL-MULTIMOORA method and the hesitant fuzzy linguistic TOPSIS method are provided to show the advantages of the proposed method. © 2017 Elsevier B.V. All rights reserved. l p v t t s c e P t t g
Global H∞ Consensus of Multi-Agent Systems with Lipschitz Nonlinear Dynamics

Abstract: This paper addresses the global consensus problems of a class of nonlinear multi-agent systems with Lipschitz nonlinearity and directed communication graphs, by using a distributed consensus protocol based on the relative states of neighboring agents. A two-step algorithm is presented to construct a protocol, under which a Lipschitz multi-agent system without disturbances can reach global consensus for a strongly connected directed communication graph. Another algorithm is then given to design a protocol which can achieve global consensus with a guaranteed H∞ performance for a Lipschitz multiagent system subject to external disturbances. The case with a leader-follower communication graph is also discussed. Finally, the effectiveness of the theoretical results is demonstrated through a network of single-link manipulators.
Risks and benefits of social media for children and adolescents.

Resources • AAP Internet safety resources site, http:// safetynet.aap.org • CDC Social Media Tools Guidelines & Best Practices site, http://www.cdc.gov/ SocialMedia/Tools/ guidelines/ • Common Sense Media (2009). Is technology changing childhood? A national poll on teens and social networking. R e t r i e v e d f r om http://www.commonsensemedia.org/teensocial-media. FACEBOOK, TWITTER, AND YouTube bring benefits to children and teenagers, including enhancing communication, broadening social connections, and learning technical skills, but can also expose them to risks, such as cyberbullying, “Facebook depression,” and “sexting,” according to a new report by the American Academy of Pediatrics (AAP; O'Keeffe, Clarke-Pearson, & Council on Communications and Media, 2011). The new report outlines the latest research on one of the most common activities among today's children and teenagers and describes how health care providers can help families understand these sites and encourage their healthy use. The report considers any site that allows social interaction as a social media site, including social networking sites such as Facebook, MySpace, and Twitter; gaming sites and virtual worlds such as Club Penguin, Second Life, and the Sims; video sites such as YouTube; and blogs. The abundance of these sites has grown exponentially in recent years. According to a poll cited in the report, more than half of American teenagers log onto their favorite social media site at least once a day, whereas 22% do so at least 10 times a day; 75% of teenagers now own cell phones, with 54% of them using them for texting, 24% for instant messaging, and 25% for social media access. According to the authors of the new report, increase in social media has been so rapid and their presence in children's everyday life is now so pervasive that, for some teens, social media is the primary way they interact socially, and a large part of this generation's social and emotional development is occurring while on the Internet and on cell phones. Because of their limited capacity for self-regulation and susceptibility to peer pressure,
A 600MS/s 30mW 0.13µm CMOS ADC array achieving over 60dB SFDR with adaptive digital equalization

At high conversion speed, time interleaving provides a viable way of achieving analog-to-digital conversion with low power consumption, especially when combined with the successive-approximation-register (SAR) architecture that is known to scale well in CMOS technology. In this work, we showcase a digital background-equalization technique to treat the path-mismatch problem as well as individual ADC nonlinearities in time-interleaved SAR ADC arrays. This approach was first introduced to calibrate the linearity errors in pipelined ADCs [1], and subsequently extended to treat SAR ADCs [2]. In this prototype, we demonstrate the effectiveness of this technique in a compact SAR ADC array, which achieves 7.5 ENOB and a 65dB SFDR at 600MS/s while dissipating 23.6mW excluding the on-chip DLL, and exhibiting one of the best conversion FOMs among ADCs with similar sample rates and resolutions [3].
Supernumerary nostril: a case report

BACKGROUND
Supernumerary nostril is a congenital anomaly that contains additional nostril with or without accessory cartilage. These rare congenital nasal deformities result from embryological defects. Since 1906, Lindsay (Trans Pathol Soc Lond. 57:329-330, 1906) has published the first research of bilateral supernumerary nostrils, and only 34 cases have been reported so far in the English literature.


CASE PRESENTATION
A 1-year-old female baby was brought to our department group for the treatment of an accessory opening above the left nostril which had been presented since her birth. Medical history was non-specific and her birth was normal. The size of a supernumerary nostril was about 0.2 cm diameter and connected to the left nostril. The right one was normal. Minimal procedure was operated for the anomaly. After 1 year, rhinoplasty was performed for the nostril asymmetry.


CONCLUSIONS
At 1 year follow-up, the functional and cosmetic result was satisfactory. In this case, it is important that we have early preoperative diagnosis. Also, it is desirable that we should perform a corrective surgery as soon as possible for the patient's psychosocial growth.