Miracle-dz/UniFAR-FTUs huggingface dataset:
Long Range LiDAR Characterisation for Obstacle Detection for use by the Visually Impaired and Blind

Obstacle detection and avoidance is a huge area of interest for autonomous vehicles and, as such, has become an important research topic. Detecting and identifying obstacles enables navigation through an ever changing environment. This work looks at the technology used in self-driving vehicles and examines whether the same technology could be used to aid in navigation for visually impaired and blind (VIB) people. For autonomous vehicles, obstacle detection relies on different sensor modalities to provide information on the vehicles surroundings. A combination of the same sensors placed on a white cane could be used to perform free-space assessment over the whole height of the user and provide additional environmental information not available from the cane alone. This provides its own challenges and advantages. The speeds are much slower when dealing with pedestrians and scanning can be achieved by the movement of the cane. However, the weight and size must be significantly reduced. The full system will be integrated into a smart cane and will consist of four main sensors as well as range sensors. The aim of this work is to report on the characterisation of a long range LiDAR (up to 10m) that will be integrated into a smart white cane developed as part of the INSPEX H2020 project.
Invited Paper: Local Differential Privacy on Metric Spaces: Optimizing the Trade-Off with Utility

Local differential privacy (LPD) is a distributed variant of differential privacy (DP) in which the obfuscation of the sensitive information is done at the level of the individual records, and in general it is used to sanitize data that are collected for statistical purposes. LPD has the advantage it does not need to assume a trusted third party. On the other hand LDP in general requires more noise than DP to achieve the same level of protection, with negative consequences on the utility. In practice, utility becomes acceptable only on very large collections of data, and this is the reason why LDP is especially successful among big companies such as Apple and Google, which can count on a huge number of users. In this talk, we propose a variant of LDP suitable for metric spaces, such as location data or energy consumption data, and we show that it provides a much higher utility for the same level of privacy. Furthermore, we discuss algorithms to extract the best possible statistical information from the data obfuscated with this metric variant of LDP.
Benchmarking in Manipulation Research: The YCB Object and Model Set and Benchmarking Protocols

In this paper we present the Yale-CMU-Berkeley (YCB) Object and Model set, intended to be used to facilitate benchmarking in robotic manipulation, prosthetic design and rehabilitation research. The objects in the set are designed to cover a wide range of aspects of the manipulation problem; it includes objects of daily life with different shapes, sizes, textures, weight and rigidity, as well as some widely used manipulation tests. The associated database provides highresolution RGBD scans, physical properties, and geometric models of the objects for easy incorporation into manipulation and planning software platforms. In addition to describing the objects and models in the set along with how they were chosen and derived, we provide a framework and a number of example task protocols, laying out how the set can be used to quantitatively evaluate a range of manipulation approaches including planning, learning, mechanical design, control, and many others. A comprehensive literature survey on existing benchmarks and object datasets is also presented and their scope and limitations are discussed. The set will be freely distributed to research groups worldwide at a series of tutorials at robotics conferences, and will be otherwise available at a reasonable purchase cost. It is our hope that the ready availability of this set along with the ground laid in terms of protocol templates will enable the community of manipulation researchers to more easily compare approaches as well as continually evolve benchmarking tests as the field matures.
Highly Productive Solder Interconnect Formation by Bump Stabbing for 3D-TSV Die Stacking

New high speed die stacking process using the originally designed stabbing pad combined with mass reflow for 2.5D and 3D has been developed. The top die having the bump of Cu pillar and solder cap was picked and placed on the bottom die which has the stabbing pad. The bump was stabbed by the pad with aligned. The stabbing pad has columns of 3 to 4 µm height, which were plated Cu coated by Ni/Au. The stabbing step took only 0.1 second. Well wetted solder joint between the bump the stabbing pad was formed. Sn-Ni-Cu alloy layer was detected by cross sectional EDX analysis at the interface of the column and the solder. Numerical analysis by finite element method revealed that the advantage of the bump stabbing process of the lower stress around the joint during reflow process comparing with TCB. The estimated UPH is 1440, which is much higher than that of conventional TCB process.
A 375 nA Input Off Current Schmitt Triger LDO for Energy Harvesting IoT Sensors

This paper introduces 375 nA input off current Schmitt trigger LDO, which is suitable for receiving the power from high internal impedance energy harvesting power sources. The Schmitt trigger LDO consumes 375nA input current at the input voltage of 0.5V, and occupies 276 x 295 um area using 0.18 um CMOS technology. The proposed Schmitt trigger LDO is used to make an Energy Harvesting Illumination Beat Sensor Node, so that the sensor node wirelessly transmits the data of illumination from 780 to 1540 lx without battery.
CUBE: A scalable framework for large-scale industrial simulations

Writing high-performance solvers for engineering applications is a delicate task. These codes are often developed on an application to application basis, highly optimized to solve a certain problem. Here, we present our work on developing a general simulation framework for efficient computation of time-resolved approximations of complex industrial flow problems—Complex Unified Building cube method (CUBE). To address the challenges of emerging, modern supercomputers, suitable data structures and communication patterns are developed and incorporated into CUBE. We use a Cartesian grid together with various immersed boundary (IB) methods to accurately capture moving, complex geometries. The asymmetric workload of the IB is balanced by a predictive dynamic load balancer, and a multithreaded halo exchange algorithm is employed to efficiently overlap communication with computations. Our work also concerns efficient methods for handling the large amount of data produced by large-scale flow simulations, such as scalable parallel I/O, data compression, and in-situ processing.
Efficient and Privacy-Preserving Proximity Detection Schemes for Social Applications

With the pervasiveness of location-aware mobile terminals and the popularity of social applications, location-based social networking service (LBSNS) has brought great convenience to people’s life. Meanwhile, proximity detection, which makes LBSNS more flexible, has aroused widespread concern. However, the prosperity of LBSNS still faces many severe challenges on account of users’ location privacy and data security. In this paper, we propose two efficient and privacy-preserving proximity detection schemes, named arbitrary geometric range query for polygons (AGRQ-P) and arbitrary geometric range query for circles (AGRQ-C), for location-based social applications. With proposed schemes, a user can choose any area on the map, and query whether her/his friends are within the region without divulging the query information to both social application servers and other users, meanwhile, the accurate locations of her/his friends are also confidential for the servers and the query user. Specifically, with algorithms based on ciphertext of geometric range query, users’ query and location information is blurred into ciphertext in client, thus no one but the user knows her/his own sensitive information. Detailed security analysis shows that various security threats can be defended. In addition, the proposed schemes are implemented in an IM APP with a real LBS dataset, and extensive simulation results over smart phones further demonstrate that AGRQ-P and AGRQ-C are highly efficient and can be implemented effectively.
Comparison of PD‐L1 immunohistochemistry assays and response to PD‐1/L1 inhibitors in advanced non‐small‐cell lung cancer in clinical practice

Several studies have demonstrated analytical comparability between different PD‐L1 assays, but their clinical validity in non‐small‐cell lung cancer in terms of response to treatment outside clinical trials has not been established. The aim of our study is to assess the analytical performance of laboratory‐developed tests for Ventana SP263 and Agilent/Dako 22C3, and to investigate the association between PD‐L1 assays and response to PD‐1/L1 inhibitors.
Shortest (A+B)-path packing via hafnian

Bj\"orklund and Husfeldt developed a randomized polynomial time algorithm to solve the shortest two disjoint paths problem. Their algorithm is based on computation of permanents modulo 4 and the isolation lemma. In this paper, we consider the following generalization of the shortest two disjoint paths problem, and develop a similar algebraic algorithm. The shortest perfect $(A+B)$-path packing problem is: given an undirected graph $G$ and two disjoint node subsets $A,B$ with even cardinalities, find a shortest $|A|/2+|B|/2$ disjoint paths whose ends are both in $A$ or both in $B$. Besides its NP-hardness, we prove that this problem can be solved in randomized polynomial time if $|A|+|B|$ is fixed. Our algorithm basically follows the framework of Bj\"orklund and Husfeldt but uses a new technique: computation of hafnian modulo $2^k$ combined with Gallai's reduction from $T$-paths to matchings. We also generalize our technique for solving other path packing problems, and discuss its limitation.
On Problems as Hard as CNFSAT

The ﬁeld of exact exponential time algorithms for NP-hard problems has thrived over the last decade. While exhaustive search remains asymptotically the fastest known algorithm for some basic problems, diﬃcult and non-trivial exponential time algorithms have been found for a myriad of problems, including Graph Coloring , Hamiltonian Path , Dominating Set and 3- CNF-Sat . In some instances, improving these algorithms further seems to be out of reach. The CNF-Sat problem is the canonical example of a problem for which the trivial exhaustive search algorithm runs in time O (2 n ), where n is the number of variables in the input formula. While there exist non-trivial algorithms for CNF-Sat that run in time o (2 n ), no algorithm was able to improve the growth rate 2 to a smaller constant, and hence it is natural to conjecture that 2 is the optimal growth rate. The strong exponential time hypothesis (SETH) by Impagliazzo and Paturi [JCSS 2001] goes a little bit further and asserts that, for every (cid:15) < 1, there is a (large) integer k such that k - CNF-Sat cannot be computed in time 2 (cid:15)n . In this paper, we show that, for every (cid:15) < 1, the problems Hitting Set , Set Splitting , and NAE-Sat cannot be computed in time O (2 (cid:15)n ) unless SETH fails. Here n is the number of elements or variables in the input. For these problems, we actually get an equivalence to SETH in a certain sense. We conjecture that SETH implies a similar statement for Set Cover , and prove that, under this assumption, the fastest known algorithms for Steiner Tree , Connected Vertex Cover , Set Partitioning , and the pseudo-polynomial time algorithm for Subset Sum cannot be signiﬁcantly improved. Finally, we justify our assumption about the hardness of Set Cover by showing
Classified texture resizing for mobile devices

Power consumption is one of the most important factors in mobile computing. Especially for high-quality games, it takes a lot of computing power to render visual effects. In order to reduce this, some rendering techniques (e.g., Samsung Game Tuner) adjust rendering parameters (screen resolution, frame rates, and texture sizes) to improve power efficiency or performance. Among them, the texture resizing reduces power consumption in some cases, but it sometimes results in poor rendering quality or no energy saving. To improve the texture resizing, we present the classified texture resizing technique. Our main idea is to classify textures into certain types and to apply a different approach to each type. As a result, our approach minimizes degradation of rendering quality and can be applied to wider applications. Our experimental results show up to 16% power reduction of a GPU and DRAM.
Wavelet methods for combining CAD with enhancement of mammograms

Computer-aided diagnosis techniques have been proposed as second opinion providers in digital mammography. This paper considers a new method of presenting CAD output to the radiologist. Instead of superimposing detected pixels or arrows on the mammogram, we adaptively enhance the most suspicious regions according to the weight indicated by the test statistic at the detector output. In so doing, CAD false positives promise to be less obtrusive to the viewer, and lesions missed by CAD (false negatives) may still be detected by the radiologist. In our method the entire mammogram is enhanced to some (spatially varying) degree. Enhancement is realized by applying nonlinear operators to wavelet coefficients computed at multiple scales. We combine this technique with the results of our previous wavelets-based CAD algorithm for detecting microcalcifications.
Design of a Compact Broadband Butler Matrix and Its Application in Organic Beam-Former at the 5 GHz Band

Unlicensed spectrum at 5 GHz, from 5.15 GHz to 5.85 GHz, has been proposed by multiple countries as the U-NII (Unlicensed National Information Infrastructure) radio band to be used by IEEE-802.11a. This frequency band of interest of 5 GHz can also be potentially applicable to 5G (the Fifth Generation, a commercial system operating on licensed bands) wireless wide area network (WAN) systems. The 5 GHz band is relatively clean, as compared to the overly crowded 2.45 GHz band. Our space-efficient beamforming design is based on this band. The bandwidth of the patch antennas used in the beam-former was designed to be 0.7 GHz; at the center frequency of 5.5 GHz, it is 13% of the center frequency. Any designed system that satisfies this percentage can be considered as a broadband system. In this paper, we first discuss a preliminary Proof of Concept (two double-layer organic boards) design, then show the preliminary results; and lastly discuss the design improvement (Section IV).
Innovation of Human Resources Development by M-Learning to Support Cross-border Tourism Event in Natuna

Natuna has a great potential of natural resources, and its main potential is tourism. The development of cross-border tourism is in line with Jokowi-Jusuf Kalla's nine priorities. However, the obstacle in tourism is human resources who fluently speak foreign languages in marketing and communicating with foreign tourists, especially in the border area. Since Natuna is far and difficult to reach, no Natuna's university educates their human resources to speak a foreign language and because Natuna is also lack of foreign teacher. Therefore, it needs a breakthrough in foreign language learning through mobile learning applications. As smartphones are commonly used in society, the solution of foreign language learning through smartphone application became an innovation in education and training. The research method was Focus Group Discussion (FGD) between officials of Natuna's Regional Planning, Research, and Development Agency. The FGD was done by showing the design of interactive mobile applications for foreign language learning, especially English and Mandarin. The design of this application has been demonstrated in the FGD activities and has received a positive response. The conclusion of this research is Mobile Learning application is a foreign language learning solution to support tourism activities in Natuna.
Context-Aware Cloud Robotics for Material Handling in Cognitive Industrial Internet of Things

In the context of Industry 4.0, industrial robotics such as automated guided vehicles have drawn increased attention due to their automation capabilities and low cost. With the support of cognitive technologies for industrial Internet of Things (IoT), production processes can be significantly optimized and more intelligent manufacturing can be implemented for smart factories. In this paper, for advanced material handling, a cognitive industrial entity called context-aware cloud robotics (CACR) are introduced and analyzed. Compared with the one-time on-demand delivery, CACR is characterized by two features: 1) context-aware services and 2) effective load balancing. First, the system architecture, advantages, challenges, and applications for CACR are introduced. Then, fundamental functions for material handling are articulated, namely, decision-making mechanisms and cloud-enabled simultaneous localization and mapping. Finally, a CACR case study is performed to highlight its energy-efficient and cost-saving material handling capabilities. Simulations indicate the superiority of cognitive industrial IoT and show that using CACR for material handling can significantly improve energy efficiency and save cost.
Mentoring as information practice: Unpacking the black box

Formal mentoring is an increasingly popular tool for professional development and socialization, particularly in higher education, where expertise is contextual and dynamic. As it is currently enacted, however, mentoring suffers from a lack of clarity, as each participant – protégé or mentor – seems to have a different understanding of what mentoring is or should be. If mentor and protégé don't have the same understanding, necessary mentoring may not take place. The challenge for researchers is that the action of mentoring usually takes place in dyadic privacy. Studies of mentoring therefore focus on outcomes and participant satisfaction, without being able to separate the links between mentoring functions and those outcomes. In this paper I propose a model of the mentoring relationship that describes the information practices of mentoring. This model is derived from a study of faculty mentors at a large mid‐Atlantic university. The model will extend our understanding of mentoring by applying the concept of information practices to the mentoring process.
Sugar and energy content of carbonated sugar-sweetened beverages in Haidian District, Beijing: a cross-sectional study

Objective The consumption of carbonated sugar-sweetened beverages (CSSBs) is associated with a range of health problems, but little is known about the sugar and energy content of CSSBs in China. The study aimed to investigate the sugar and energy content of CSSBs in Beijing, China. Study design We carried out a cross-sectional survey in 15 different supermarkets from July to October 2017 in Haidian District, Beijing. Methods The product packaging and nutrient labels of CSSBs were recorded by a snapshot in time to obtain company name, product name, serving size, and nutrient content, that is, carbohydrate, sugar and energy. For CSSB labels not showing sugar content, we used carbohydrate content as substitute. The sugar and energy content of CSSBs within each type of flavour were compared using Kruskal-Wallis test. The sugar content within the recommended levels was described using frequency. We also compared the sugar and energy content of top 5 CSSBs in terms of sales among three countries (China, UK and USA). Results A total of 93 CSSB products were found. The median sugar content was 9.3 (IQR: 5.7–11.2) g/100 mL, and the energy content was 38 (IQR: 23–46) kcal/100 mL. There were 79 products labelled ‘Red’ (high) per serving based on the criteria set in the UK (>11.25 g/100 mL). We found 62.4% of CSSBs had sugar content per serving that exceeds the daily free sugar intake for adults (25 g) recommended by the WHO. Some of the branded products sold in China had higher sugar content when they were compared with those in Western countries. Conclusions CSSBs in Beijing, China have high sugar and energy content. Reduction in sugar content and serving size of CSSBs and taxation policy on beverages will be beneficial in reducing sugar intake in China.
Neural network for software reliability analysis of dynamically weighted NHPP growth models with imperfect debugging

This paper propose a learning algorithm of supervised back‐propagation neural networks for dynamic weighted combination of software reliability model. The proposed model is an assimilation of 3 well‐known non‐homogeneous poisson process (NHPP)–based software reliability growth models with imperfect debugging. The novel approach of proposed supervised back propagation–based neural network 2‐stage architecture has a great impact on the network by combining the imperfect debugging models based on the nature of fault introduction rate during testing and debugging. Function approximation metrics are used for comparing the proposed model with individual models. Three data sets are trained using supervised back‐propagation neural networks to compare the performance and validity evaluation of proposed and existing NHPP models and dynamic weighted combinational model. Reliability analysis among important NHPP models incorporating imperfect debugging is illustrated through numerical and graphical explanation of several metrics using supervised back‐propagation neural networks.
Ransomware's Early Mitigation Mechanisms

Ransomware remains a modern trend. Attackers are still using cryptovirology forcing victims to pay. Notable attacks have been spreading since 2012, starting with Reveton's ransomware attack to the more recent 2017 WannaCry, Petya and Bad Rabbit cyberattacks. This Ransomware as a Service (RaaS) can lure criminals into developing tools to perform an attack without previous knowledge of the cryptosystem itself. We present in this paper a graph-based ransomware countermeasure to detect malicious threads. It is a new mechanism that doesn't rely on previously used metrics in the literature to detect ransomware such as Shannon's entropy or system calls. An accurate detection is achieved by our solution. The per-thread file system traversal is sufficient to highlight the malicious behaviors. To the best of our knowledge, no previous study has been conducted in this area. The ransomware collection used in our experiments contains more than 700 active examples of ransomware, that were analyzed in our bar metal sandbox environment.