nils-herrmann/clean_scirepeval huggingface dataset:
A Survey on Artificial Intelligence and Robotics

Today many multi-national companies or organizations are adopting the use of automation. Automation means replacing the human by intelligent robots or machines which are capable to work as human (may be better than human). Artificial intelligence is a way of making machines, robots or software to think like human. As the concept of artificial intelligence is use in robotics, it is necessary to understand the basic functions which are required for robots to think and work like human. These functions are planning, acting, monitoring, perceiving and goal reasoning. These functions help robots to develop its skills and implement it. Since robotics is a rapidly growing field from last decade, it is important to learn and improve the basic functionality of robots and make it more useful and user-friendly.
Minimizing power consumption in digital CMOS circuits

An approach is presented for minimizing power consumption for digital systems implemented in CMOS which involves optimization at all levels of the design. This optimization includes the technology used to implement the digital circuits, the circuit style and topology, the architecture for implementing the circuits and at the highest level the algorithms that are being implemented. The most important technology consideration is the threshold voltage and its control which allows the reduction of supply voltage without signijcant impact on logic speed. Even further supply reductions can be made by the use of an architecture-based voltage scaling strategy, which uses parallelism and pipelining, to tradeoff silicon area and power reduction. Since energy is only consumed when capacitance is being switched, power can be reduced by minimizing this capacitance through operation reduction, choice of number representation, exploitation of signal correlations, resynchronization to minimize glitching, logic design, circuit design, and physical design. The low-power techniques that are presented have been applied to the design of a chipset for a portable multimedia terminal that supports pen input, speech I/O and fullmotion video. The entire chipset that perjorms protocol conversion, synchronization, error correction, packetization, buffering, video decompression and D/A conversion operates from a 1.1 V supply and consumes less than 5 mW.
By-Phrases in Passives and Nominals ∗

A longstanding claim in the literature holds that by-phras es are special in the passive, receiving certain external argument roles that by-phrases in nominals cannot, for inst ance the role of experiencer. This paper challenges this lon gsta ding claim and shows that by-phrases are not special in the passiv e: they can receive all of the thematic roles that they can in v erbal passives. They are banned from certain nominals for the same reason they are banned from certain VP types like unaccusati ve and sporadic advancements: by-phrases require the syntact ic and semantic presence of an external argument. By-phrase s c n receive a uniform analysis, whether they occur with verbs or in nominals. The analysis proposed here involves syntactic word formation, with syntactic heads effecting passivization a nd nominalization. It also relies on syntactic selection fo r selectional features, and proposes a theory of such features. The concep tion of grammar that emerges is one without lexical rules, wh ere passivization and nominalization take place in the syntax.
Identity construction on Facebook: Digital empowerment in anchored relationships

Early research on online self-presentation mostly focused on identity constructions in anonymous online environments. Such studies found that individuals tended to engage in role-play games and anti-normative behaviors in the online world. More recent studies have examined identity performance in less anonymous online settings such as Internet dating sites and reported different findings. The present study investigates identity construction on Facebook, a newly emerged nonymous online environment. Based on content analysis of 63 Facebook accounts, we find that the identities produced in this nonymous environment differ from those constructed in the anonymous online environments previously reported. Facebook users predominantly claim their identities implicitly rather than explicitly; they ‘‘show rather than tell” and stress group and consumer identities over personally narrated ones. The characteristics of such identities are described and the implications of this finding are discussed.
OFDM for Optical Communications

Orthogonal frequency division multiplexing (OFDM) is a modulation technique which is now used in most new and emerging broadband wired and wireless communication systems because it is an effective solution to intersymbol interference caused by a dispersive channel. Very recently a number of researchers have shown that OFDM is also a promising technology for optical communications. This paper gives a tutorial overview of OFDM highlighting the aspects that are likely to be important in optical applications. To achieve good performance in optical systems OFDM must be adapted in various ways. The constraints imposed by single mode optical fiber, multimode optical fiber and optical wireless are discussed and the new forms of optical OFDM which have been developed are outlined. The main drawbacks of OFDM are its high peak to average power ratio and its sensitivity to phase noise and frequency offset. The impairments that these cause are described and their implications for optical systems discussed.
Towards Secure and Privacy-Preserving Data Sharing in e-Health Systems via Consortium Blockchain

Electronic health record sharing can help to improve the accuracy of diagnosis, where security and privacy preservation are critical issues in the systems. In recent years, blockchain has been proposed to be a promising solution to achieve personal health information (PHI) sharing with security and privacy preservation due to its advantages of immutability. This work proposes a blockchain-based secure and privacy-preserving PHI sharing (BSPP) scheme for diagnosis improvements in e-Health systems. Firstly, two kinds of blockchains, private blockchain and consortium blockchain, are constructed by devising their data structures, and consensus mechanisms. The private blockchain is responsible for storing the PHI while the consortium blockchain keeps records of the secure indexes of the PHI. In order to achieve data security, access control, privacy preservation and secure search, all the data including the PHI, keywords and the patients’ identity are public key encrypted with keyword search. Furthermore, the block generators are required to provide proof of conformance for adding new blocks to the blockchains, which guarantees the system availability. Security analysis demonstrates that the proposed protocol can meet with the security goals. Furthermor, we implement the proposed scheme on JUICE to evaluate the performance.
Focus+Context Display and Navigation Techniques for Enhancing Radial, Space-Filling Hierarchy Visualizations

Radial, space-filling visualizations can be useful for depi cting information hierarchies, but they suffer from one major problem. As the hierarchy grows in size, ma ny items become small, peripheral slices that are difficult to distinguish. We have developed t hree visualization/interaction techniques that provide flexible browsing of the display. The technique s allow viewers to examine the small items in detail while providing context within the entire in formation hierarchy. Additionally, smooth transitions between views help users maintain orientation within the complete information space.
Digital droplets: Microsoft SkyDrive forensic data remnants

Cloud storage services such as the popular Microsoft© SkyDrive© provide both organisational and individual users a cost-effective, and in some cases free, way of accessing, storing and disseminating data. The identification of digital evidence relating to cloud storage services can, however, be a challenge in a digital forensic investigation. Using SkyDrive as a case study,we identified the types of terrestrial artefacts that are likely to remain on a client’s machine (in the context of our experiments; computer hard drive and iPhone), and where the access point(s) for digital forensics examiners are, that will allow them to undertake steps to secure evidence in a timely fashion.
CORPORATE SOCIAL RESPONSIBILITY : REWRITING THE RELATIONSHIP BETWEEN BUSINESS AND SOCIETY

The relationship between business and society has witnessed a dramatic change in the past few years. Globalization, ethical consumerism, environmental concerns, strict government regulations, and growing strength of the civil society, are all factors that forced businesses to reconsider their role in society; accordingly there has been a surge of notions that tries to explain this new complex relation between business and society. This paper aims at accentuating this evolving relation by focusing on the concept of corporate social responsibility (CSR). It differentiates between CSR and other related concepts such as business ethics and corporate philanthropy. It analyzes the different arguments in the CSR debate, pinpoints mechanisms adopted by businesses in carrying out their social responsibilities, and concludes with the link between corporate social responsibility and sustainable development.
Getting it right the second time.

Once a business performs a complex activity well, the parent organization often wants to replicate that success. But doing that is surprisingly difficult, and businesses nearly always fail when they try to reproduce a best practice. The reason? People approaching best-practice replication are overly optimistic and overconfident. They try to perfect an operation that's running nearly flawlessly, or they try to piece together different practices to create the perfect hybrid. Getting it right the second time (and all the times after that) involves adjusting for overconfidence in your own abilities and imposing strict discipline on the process and the organization. The authors studied numerous business settings to find out how organizational routines were successfully reproduced, and they identified five steps for successful replication. First, make sure you've got something that can be copied and that's worth copying. Some processes don't lend themselves to duplication; others can be copied but maybe shouldn't be. Second, work from a single template. It provides proof success, performance measurements, a tactical approach, and a reference for when problems arise. Third, copy the example exactly, and fourth, make changes only after you achieve acceptable results. The people who developed the template have probably already encountered many of the problems you want to "fix," so it's best to create a working system before you introduce changes. Fifth, don't throw away the template. If your copy doesn't work, you can use the template to identify and solve problems. Best-practice replication, while less glamorous than pure innovation, contributes enormously to the bottom line of most companies. The article's examples--Banc One, Rank Xerox, Intel, Starbucks, and Re/Max Israel--prove that exact copying is a non-trivial, challenging accomplishment.
SWOT ANALYSIS Strategic Planning Session October 21 , 2008 Community Sector Strengths :

Community Sector Strengths: Diversity in health promotion team Interest and commitment to cause Walkability training is completed Opportunity to build upon past policies – smoke free History of HCC Outreach completed to date Connectedness of partners Name/community recognition –branded Support from leaders Resources and capacity Support to communities We know the players in the communities Grant writing capabilities and previous experience Diversity in experience in projects and expertise in HCC Assessment and Data collection completed to date
Face Recognition Techniques : A Survey

Face is the index of mind. It is a complex multidimensional structure and needs a good computing technique for recognition. While using automatic system for face recognition, computers are easily confused by changes in illumination, variation in poses and change in angles of faces. A numerous techniques are being used for security and authentication purposes which includes areas in detective agencies and military purpose. These surveys give the existing methods in automatic face recognition and formulate the way to still increase the performance.
Project management in a software product line organization

In traditional software engineering project management, managers provide focused guidance to a team responsible for producing a specific result in a specified amount of time. Today, however, organizations are increasingly taking a product line approach to software to exploit product commonalities. Software product line organizations have unique practices and project definitions. These unconventional features offer new challenges and directions for traditional project management. How does the traditional concept of a project - a temporary endeavor aimed at creating a unique product or service - hold up under this new paradigm? In this article, we discuss this question, along with how the idea of a "project" and project management techniques must expand to fit a product line context. In particular, we show how the "overall guidelines, policies, and procedures" that Thayer and Pyster spoke of some years ago remain crucially important in product line organizations today.
Analysis of Layered Social Networks

It is a premise of this research that prevention of near-term terrorist attacks requires an understanding of current terrorist organizations to include their composition, the actors involved, and how they operate to achieve their objectives. To aid in this understanding, operations research, sociological, and behavioral theory relevant to the study of social networks are applied, thereby providing theoretical foundations for new and useful methodologies to analyze non-cooperative organizations. Such organizations are defined as those trying to hide their structures or are unwilling to provide information regarding their operations; examples include criminal networks, secret societies, and, most importantly, clandestine terrorist organizations. Techniques leveraging information regarding multiple dimensions of interpersonal relationships, inferring from them the strengths of interpersonal ties, are explored. Hence, a layered network construct is offered that provides new analytic opportunities and insights generally unaccounted for in traditional social network analysis. These offer decision makers improved courses of action designed to impute influence upon an adversarial network, thereby achieving a desired influence, perception, or outcome to one or more actors within the target network. In addition, this knowledge can also be used to identify key individuals, relationships, and organizational practices. Subsequently, such analysis may lead to the identification of weaknesses that can be exploited in an endeavor to either eliminate the network as a whole, cause it to become operationally ineffective, or influence it to directly or indirectly support National Security Strategy. In today’s world, proficiency in this aspect of warfare is a necessary condition to ensure United States National Security, as well as to promote and maintain global stability. Quantitative methods serving as the basis for, and discriminator between, courses of action seeking a path towards peace are a principal output of this research.
Simple Does It: Weakly Supervised Instance and Semantic Segmentation

Semantic labelling and instance segmentation are two tasks that require particularly costly annotations. Starting from weak supervision in the form of bounding box detection annotations, we propose a new approach that does not require modification of the segmentation training procedure. We show that when carefully designing the input labels from given bounding boxes, even a single round of training is enough to improve over previously reported weakly supervised results. Overall, our weak supervision approach reaches ~95% of the quality of the fully supervised model, both for semantic labelling and instance segmentation.
A Quantitative Analysis of Developer Information Needs in Software Ecosystems

We present the results of an investigation into the nature of information needs of software developers who work in projects that are part of larger ecosystems. This work is based on a quantitative survey of 75 professional software developers. We corroborate the results identified in the survey with needs and motivations proposed in a previous survey and discover that tool support for developers working in an ecosystem context is even more meager than we thought: mailing lists and internet search are the most popular tools developers use to satisfy their ecosystem-related information needs.
Semantic-based lightweight ontology learning framework: a case study of intrusion detection ontology

Building ontology for wireless network intrusion detection is an emerging method for the purpose of achieving high accuracy, comprehensive coverage, self-organization and flexibility for network security. In this paper, we leverage the power of Natural Language Processing (NLP) and Crowdsourcing for this purpose by constructing lightweight semi-automatic ontology learning framework which aims at developing a semantic-based solution-oriented intrusion detection knowledge map using documents from Scopus. Our proposed framework uses NLP as its automatic component and Crowdsourcing is applied for the semi part. The main intention of applying both NLP and Crowdsourcing is to develop a semi-automatic ontology learning method in which NLP is used to extract and connect useful concepts while in uncertain cases human power is leveraged for verification. This heuristic method shows a theoretical contribution in terms of lightweight and timesaving ontology learning model as well as practical value by providing solutions for detecting different types of intrusions.
Spatio-Temporal Data Mining for Climate Data : Advances , Challenges , and Opportunities

Our planet is experiencing simultaneous changes in global population, urbanization, and climate. These changes, along with the rapid growth of climate data and increasing popularity of data mining techniques may lead to the conclusion that the time is ripe for data mining to spur major innovations in climate science. However, climate data bring forth unique challenges that are unfamiliar to the traditional data mining literature, and unless they are addressed, data mining will not have the same powerful impact that it has had on fields such as biology or e-commerce. In this chapter, we refer to spatio-temporal data mining (STDM) as a collection of methods that mine the data’s spatio-temporal context to increase an algorithm’s accuracy, scalability, or interpretability (relative to non-space-time aware algorithms). We highlight some of the singular characteristics and challenges STDM faces within climate data and their applications, and provide the reader with an overview of the advances in STDM and related climate applications. We also demonstrate some of the concepts introduced in the chapter’s earlier sections with a real-world STDM pattern mining application to identify mesoscale ocean eddies from satellite data. The case-study provides the reader with concrete examples of challenges faced when mining climate data and how effectively analyzing the data’s spatio-temporal context may improve existing methods’ accuracy, interpretability, and scalability. We end the chapter with a discussion of notable opportunities for STDM research within climate. James H. Faghmous Department of Computer Science and Engineering, The University of Minnesota – Twin Cities e-mail: jfagh@cs.umn.edu Vipin Kumar Department of Computer Science and Engineering, The University of Minnesota – Twin Cities e-mail: kumar@cs.umn.edu
LAG: Lazily Aggregated Gradient for Communication-Efficient Distributed Learning

This paper presents a new class of gradient methods for distributed machine learning that adaptively skip the gradient calculations to learn with reduced communication and computation. Simple rules are designed to detect slowly-varying gradients and, therefore, trigger the reuse of outdated gradients. The resultant gradient-based algorithms are termed Lazily Aggregated Gradient — justifying our acronym LAG used henceforth. Theoretically, the merits of this contribution are: i) the convergence rate is the same as batch gradient descent in strongly-convex, convex, and nonconvex smooth cases; and, ii) if the distributed datasets are heterogeneous (quantified by certain measurable constants), the communication rounds needed to achieve a targeted accuracy are reduced thanks to the adaptive reuse of lagged gradients. Numerical experiments on both synthetic and real data corroborate a significant communication reduction compared to alternatives.
Drone to the Rescue: Relay-Resilient Authentication using Ambient Multi-sensing

Many mobile and wireless authentication systems are prone to relay attacks whereby two non co-presence colluding entities can subvert the authentication functionality by simply relaying the data between a legitimate prover (P) and verifier (V). Examples include payment systems involving NFC and RFID devices, and zero-interaction token-based authentication approaches. Utilizing the contextual information to determine P-V proximity, or lack thereof, is a recently proposed approach to defend against relay attacks. Prior work considered WiFi, Bluetooth, GPS and Audio as different contextual modalities for the purpose of relay-resistant authentication. In this paper, we explore purely ambient physical sensing capabilities to address the problem of relay attacks in authentication systems. Specifically, we consider the use of four new sensor modalities, ambient temperature, precision gas, humidity, and altitude, for P-V proximity detection. Using an off-the-shelf ambient sensing platform, called Sensordrone, connected to Android devices, we show that combining these different modalities provides a robust proximity detection mechanism, yielding very low false positives (security against relay attacks) and very low false negatives (good usability). Such use of multiple ambient sensor modalities offers unique security advantages over traditional sensors (WiFi, Bluetooth, GPS or Audio) because it requires the attacker to simultaneously manipulate the multiple characteristics of the physical environment.