Recent Advances in Rolling 2D TMDs Nanosheets into 1D TMDs Nanotubes/Nanoscrolls

Transition metal dichalcogenides (TMDs) van der Waals (vdW) 1D heterostructures are recently synthesized from 2D nanosheets, which open up new opportunities for potential applications in electronic and optoelectronic devices. The most recent and promising strategies in regards to forming 1D TMDs nanotubes (NTs) or nanoscrolls (NSs) in this review article as well as their heterostructures that are produced from 2D TMDs are summarized. In order to improve the functionality of ultrathin 1D TMDs that are coaxially combined with boron nitride nanotubes and single-walled carbon nanotubes. 1D heterostructured devices perform better than 2D TMD nanosheets when the two devices are compared. The photovoltaic effect in WS₂ or MoS₂ NTs without a junction may exceed the Shockley–Queisser limit for the above-band-gap photovoltage generation. Photoelectrochemical hydrogen evolution is accelerated when monolayer WS₂ or MoS₂ NSs are incorporated into a heterojunction. In addition, the photovoltaic performance of the WSe₂/MoS₂ NSs junction is superior to that of the performance of MoS₂ NSs. The summary of the current research about 1D TMDs can be used in a variety of ways, which assists in the development of new types of nanoscale optoelectronic devices. Finally, it also summarizes the current challenges and prospects.     

Recognizing interleaved and concurrent activities using qualitative and quantitative temporal relationships

The majority of approaches to activity recognition in sensor environments are either based on manually constructed rules for recognizing activities or lack the ability to incorporate complex temporal dependencies. Furthermore, in many cases, the rather unrealistic assumption is made that the subject carries out only one activity at a time. In this paper, we describe the use of Markov logic as a declarative framework for recognizing interleaved and concurrent activities incorporating both input from pervasive lightweight sensor technology and common-sense background knowledge. In particular, we assess its ability to learn statistical-temporal models from training data and to combine these models with background knowledge to improve the overall recognition accuracy. We also show the viability and the benefit of exploiting both qualitative and quantitative temporal relationships like the duration of the activities and their temporal order. To this end, we propose two Markov logic formulations for inferring the foreground activity as well as each activities’ start and end times. We evaluate the approach on an established dataset where it outperforms state-of-the-art algorithms for activity recognition.     

Organic wavelength‐converting‐film‐based hybrid planar white light‐emitting diodes

Abstract— In this study, organic wavelength‐converting films (WCFs) applied to InGaN blue LED‐based hybrid planar WLED has been fabricated. The organic dye layer in the WCF was formed between the upper and bottom polymer sheets by using a simple roll‐laminating technique. Subsequently, the hybrid planar WLEDs have been fabricated based upon these films. The luminous efficiency of green WCF‐based hybrid planar WLEDs with a single blue LED chip was 34.6 lm/W and that of red‐WCF‐assisted green WCF‐based hybrid planar WLEDs was 27.3 lm/W under 20 mA. The use of WCF to fabricate hybrid planar WLEDs showed better stability than that of directly coating organic color‐convergence materials (CCMs) on the LED chips. It only decreased to about 10% of the initial wavelength‐converting intensity after 1 hour of continual operation at 20 mA.     

Compressed tag architecture for low-power embedded cache systems

Processors in embedded systems mostly employ cache architectures in order to alleviate the access latency gap between processors and memory systems. Caches in embedded systems usually occupy a major fraction of the implemented chip area. The power dissipation of cache system thus constitutes a significant fraction of the power dissipated by the entire processor in embedded systems. In this paper, we propose the compressed tag architecture to reduce the power dissipation of the tag store in cache systems. We introduce a new tag-matching mechanism by using a locality buffer and a tag compression technique. The main power reduction feature of our proposal is the use of small tag space matching instead of full tag matching, with modest additional hardware costs. The simulation results show that the proposed model provides a power and energy-delay product reduction of up to 27.8% and 26.5%, respectively, while still providing a comparable level of system performance to regular cache systems.     

CAD data visualization on mobile devices using sequential constrained Delaunay triangulation

3D graphic rendering in mobile application programs is becoming increasingly popular with rapid advances in mobile device technology. Current 3D graphic rendering engines for mobile devices do not provide triangulation capabilities for surfaces; therefore, mobile 3D graphic applications have been dealing only with pre-tessellated geometric data. Since triangulation is comparatively expensive in terms of computation, real-time tessellation cannot be easily implemented on mobile devices with limited resources. No research has yet been reported on real-time triangulation on mobile devices.In this paper, we propose a real-time triangulation algorithm for visualization on mobile devices based on sequential constrained Delaunay triangulation. We apply a compact data structure and a sequential triangulation process for visualization of CAD data on mobile devices. In order to achieve a high performance and compact implementation of the triangulation, the nature of the CAD data is fully considered in the computational process. This paper also presents a prototype implementation for a mobile 3D CAD viewer running on a handheld Personal Digital Assistant (PDA).     

Mobile-cloud assisted framework for selective encryption of medical images with steganography for resource-constrained devices

In this paper, the problem of outsourcing the selective encryption of a medical image to cloud by resource-constrained devices such as smart phone is addressed, without revealing the cover image to cloud using steganography. In the proposed framework, the region of interest of the medical image is first detected using a visual saliency model. The detected important data is then embedded in a host image, producing a stego image which is outsourced to cloud for encryption. The cloud which has powerful resources, encrypts the image and sent back the encrypted marked image to the client. The client can then extract the selectively encrypted region of interest and can combine it with the region of non-interest to form a selectively encrypted image, which can be sent to medical specialists and healthcare centers. Experimental results and analysis validate the effectiveness of the proposed framework in terms of security, image quality, and computational complexity and verify its applicability in remote patient monitoring centers.     

Legal system and its effect for prevention of work-related musculoskeletal disorders in Korea

This study aims to introduce the legislation of occupational safety and health regulations for prevention of WMSDs in Korea and investigate its effect by showing an ergonomic intervention effort in a major motor company. In Korea, WMSDs incidence rates had increased from 1999 to 2003, and it is noted that its increment jumped rapidly in 2002 and 2003. The Korean government established a law prescribing employers’ duty of preventing WMSDs in 2002, which began effective in July, 2003. Following the legislation, all employers should execute the examination of WMSDs risk factors for the eleven designated tasks every three years. In addition to this legal obligation, some large companies voluntarily established an ergonomic intervention program by carrying out in-depth assessments for stressful tasks using OWAS, RULA, NLE, etc. We introduce a major motor company case to illustrate the industry’s activities of fulfilling the legislative requirement and of performing ergonomic assessments. Thanks to Korean government and industry’s effort for prevention of WMSDs, the incidence rates of WMSDs have continually decreased from the year of 2004, right after the year when the WMSDs-related regulation was enforced.

Relevance to industry

In spite of booming of information technology industries and automation of manufacturing processes in Korea, many workers are still exposed to the risk of WMSDs including awkward postures, stressful force exertions, repetitive motions in manufacturing and agriculture industries. WMSDs cases alone constitute 43.1% of occupational diseases in Korea and the industry’s effort of ergonomic intervention of WMSDs becomes a major issue to both the management and the labor union.     

Studies on a LaF3‐coated MgO protecting layer in AC‐plasma‐display panels

A new protecting layer, a LaF₃‐coated MgO layer, in color AC‐plasma‐display panels (PDPs) was studied in order to overcome the weakness of the conventional single MgO protecting layer. The material characteristics of the new layer were examined by using variations in the deposition process. The display characteristics were also examined by implementing their processes to actual PDPs. It was demonstrated that this method is effective in lowering the firing and sustaining voltages of PDPs and enhancing the brightness of the panel as well.     

Face Detection: A Survey

In this paper we present a comprehensive and critical survey of face detection algorithms. Face detection is a necessary first-step in face recognition systems, with the purpose of localizing and extracting the face region from the background. It also has several applications in areas such as content-based image retrieval, video coding, video conferencing, crowd surveillance, and intelligent human–computer interfaces. However, it was not until recently that the face detection problem received considerable attention among researchers. The human face is a dynamic object and has a high degree of variability in its apperance, which makes face detection a difficult problem in computer vision. A wide variety of techniques have been proposed, ranging from simple edge-based algorithms to composite high-level approaches utilizing advanced pattern recognition methods. The algorithms presented in this paper are classified as either feature-based or image-based and are discussed in terms of their technical approach and performance. Due to the lack of standardized tests, we do not provide a comprehensive comparative evaluation, but in cases where results are reported on common datasets, comparisons are presented. We also give a presentation of some proposed applications and possible application areas.