nils-herrmann/clean_scirepeval huggingface dataset:
Internet of Things (IoT): A relief for Indian farmers

India is a land of different weather conditions and versatile soils. Every year Indian farmers are facing the problem of sudden rain in their areas without any correct weather forecast which leads to damage of the already grown crops. The second major problem pertaining to Indian farmers is the lack of sufficient knowledge about their soil. The soil forecasting of how the soil structure is changing day by day due to different weather condition and other external factors, and which crop will be optimally suited to be grown in such soil are some of the problems common to the farmers. This paper makes an attempt as an assessment in proposing the solution and at the same time develops a prototype of a device using IoT for the use of the farmers on Indian agricultural land. The solution proposed will have a centralized data server to analyze the data and report to the farmer the precautionary steps to be taken in advance for the safety of the crops. The solution proposed will have eco-friendly energy management through the solar plant and wind energy which make the IoT device more portable and at the same time makes implementable in any rural areas of India.
Secure and Efficient In-Hypervisor Memory Introspection Using Nested Virtualization

In JointCloud computing, the hypervisor used by each cloud plays a key role in providing services and protection for guest virtual machines (VMs). Unfortunately, the commodity hypervisor usually has a considerable attack surface and its memory is especially prone to be tampered with by an attacker who resides in one VM and then threatens the security of other co-located VMs. To mitigate such threat, previous solutions proposed an out-of-the-box design which leverages the nested virtualization to introduce a higher privileged software layer (a nested hypervisor) below the hypervisor. It also installs a security monitor into a trusted VM which is protected by the nested hypervisor and isolated from the untrusted hypervisor. The monitor is responsible for dynamically validating the behaviors of the untrusted hypervisor. Although monitoring from outside of the hypervisor can help ensure security, the large number of context switches caused by the nested virtualization incurs unacceptable overheads and makes this approach unsuitable for the cloud environment. In this paper, we introduce In-Hypervisor Memory Introspection (IHMI), an in-the-box way to monitor the hypervisor based on the nested virtualization. Our system puts the monitor into the untrusted hypervisor for efficiency while guaranteeing the same level of memory security as monitoring the hypervisor from a separated secure VM. By leveraging hardware virtualization features of current processors, IHMI isolates the monitor from the hypervisor via the nested page table and implements an efficient switch between them. Further, IHMI configures a uni-directional mapping for the monitor which allows the monitor to access the hypervisor’s memory at native speed while forbidding the hypervisor from accessing the monitor’s memory. Our IHMI system is currently still in an early stage and we report our design as well as preliminary evaluation results in this paper.
A general supervised approach to segmentation of clinical texts

Segmentation of clinical texts is critical for all sorts of tasks such as medical coding for billing, auto drafting of discharge summaries, patient problem list generation and many such applications. While there have been previous studies on using supervised approaches to segmentation of clinical texts, these existing approaches were trained and tested on a fairly limited data set showing low adaptability to new unseen documents. We propose a highly generalized supervised model for segmenting clinical texts, based on a set of line-wise predictions by a classifier with constraints imposing their coherence. Evaluation results on 5 independent test sets show that our approach can work on all sorts of note types and performs consistently across enterprises.
Occupational therapy and the use of music tempo in the treatment of the mental health care user with psychosis

Occupational therapy intervention with the client with psychosis poses a challenge to the occupational therapist and often requires both expert knowledge and an intervention strategy1. The mental health care user (MHCU) with psychosis is often treated by occupational therapists in psychiatric institutions, the location of this study. Social anxiety, attentional difficulties, impaired information processing with regard to memory and thought processes, lack of motivation (avolition), low energy and willingness to participate (anergia) and the inability to find pleasure in activities (anhedonia) are some of the symptoms that have a major impact on the occupational performance components (OPCs) of the MHCUs2. These factors also influence the occupational performance areas (OPAs) of the MHCU, like self-care and interpersonal relationships3. This is of great concern to the occupational therapist as these symptoms directly affect the reaching of occupational therapy goals. The MHCU struggles to engage in the treatment activity in such a way that all focus is limited to the stimulus at hand, thus not reaching a state of flow during the treatment session4. Furthermore, the occupational therapist is concerned about the client who is in danger of occupational deprivation where the symptoms of the psychosis keep the MHCU from using current skills and acquiring new skills in an effective way, as well as preventing the MHCU from enjoying life and activities at this stage of their illness2. In short, psychosis is a debilitating state of being that can include unwelcome additions or subtractions to life experiences2. The literature suggests that music could relieve the symptoms of psychosis5,6 and is already being used by music therapists to treat MHCUs with psychosis7. The question was raised: Could occupational therapists use this modality to treat MHCUs in an effective manner? Very limited literature exists on the use of music in occupational therapy with the treatment of patients with psychosis, setting the stage for research Occupational therapy and the use of music tempo in the treatment of the mental health care user with psychosis
A Survey on Semantic Web Technologies for the Internet of Things

The Internet of Things is a vast and growing virtual universe that includes medical devices, automobiles, industrial systems and a variable number of consumer electronics devices. With some 100 billion devices expected to be connected to the Internet by 2025, providing interoperability among the things on the IoT is one of the most fundamental requirements to support tracking, object addressing and discovery as well as information representation, storage, and exchange. Applying semantic techniques to IoT can support Interoperability, effective data access, integration resource discovery reasoning and processing of data knowledge extraction. In this paper, we present an overview of semantic technologies such as Semantic Web of Things (SWoT), Ontologies, Resource Description Framework (RDF), RDF Schema, Web Ontology Language (OWL), SPARQL Protocol And RDF Query Language (SPARQL), Semantic annotation and reasoning widely deployed in IoT.
Tunable Bandpass Filter With Two Adjustable Transmission Poles and Compensable Coupling

In this paper, tunable microstrip bandpass filters with two adjustable transmission poles and compensable coupling are proposed. The fundamental structure is based on a half-wavelength (λ/2) resonator with a center-tapped open-stub. Microwave varactors placed at various internal nodes separately adjust the filter's center frequency and bandwidth over a wide tuning range. The constant absolute bandwidth is achieved at different center frequencies by maintaining the distance between the in-band transmission poles. Meanwhile, the coupling strength could be compensable by tuning varactors that are side and embedding loaded in the parallel coupled microstrip lines (PCMLs). As a demonstrator, a second-order filter with seven tuning varactors is implemented and verified. A frequency range of 0.58-0.91 GHz with a 1-dB bandwidth tuning from 115 to 315 MHz (i.e., 12.6%-54.3% fractional bandwidth) is demonstrated. Specifically, the return loss of passbands with different operating center frequencies can be achieved with same level, i.e., about 13.1 and 11.6 dB for narrow and wide passband responses, respectively. To further verify the etch-tolerance characteristics of the proposed prototype filter, another second-order filter with nine tuning varactors is proposed and fabricated. The measured results exhibit that the tunable fitler with the embedded varactor-loaded PCML has less sensitivity to fabrication tolerances. Meanwhile, the passband return loss can be achieved with same level of 20 dB for narrow and wide passband responses, respectively.
Joint Depth Map and Color Consistency Estimation for Stereo Images with Different Illuminations and Cameras

In this paper, we propose a method that infers both accurate depth maps and color-consistent stereo images for radiometrically varying stereo images. In general, stereo matching and performing color consistency between stereo images are a chicken-and-egg problem since it is not a trivial task to simultaneously achieve both goals. Hence, we have developed an iterative framework in which these two processes can boost each other. First, we transform the input color images to log-chromaticity color space, from which a linear relationship can be established during constructing a joint pdf of transformed left and right color images. From this joint pdf, we can estimate a linear function that relates the corresponding pixels in stereo images. Based on this linear property, we present a new stereo matching cost by combining Mutual Information (MI), SIFT descriptor, and segment-based plane-fitting to robustly find correspondence for stereo image pairs which undergo radiometric variations. Meanwhile, we devise a Stereo Color Histogram Equalization (SCHE) method to produce color-consistent stereo image pairs, which conversely boost the disparity map estimation. Experimental results show that our method produces both accurate depth maps and color-consistent stereo images, even for stereo images with severe radiometric differences.
Data Mining in Education Sector : A Review

-------------------------------------------------------------------ABSTRACT------------------------------------------------------------Over the past decade there has been a rapid growth in higher education system. A lot of new institutions have come up both from public and private sector offering variety of courses for under graduating and post graduating students. The rates of enrolments for higher education has also increased but not as much as the number of higher institutions are increasing. It is a concern for today’s education system and this gap has to be identified and properly addressed to the learning community. Hence it has become important to understand the requirement of students and their academic progression. Educational Data Mining helps in a big way to answer the issues of predictions and profiling of not only students but other stake holders of education sectors. This paper discusses the application of various Data Mining tools and techniques that can be effectively used in answering the issues of predictions of student’s performance and their profiling.
Smart Management of Multiple Energy Systems in Automotive Painting Shop

Automotive painting shops consume electricity and natural gas to provide the required temperature and humidity for painting processes. The painting shop is not only responsible for a significant portion of energy consumption with automobile manufacturers, but also affects the quality of the product. Various storage devices play a crucial role in the management of multiple energy systems. It is thus of great practical interest to manage the storage devices together with other energy systems to provide the required environment with minimal cost. In this paper, we formulate the scheduling problem of these multiple energy systems as a Markov decision process (MDP) and then provide two approximate solution methods.  1 is dynamic programming with value function approximation.  2 is mixed integer programming with mean value approximation. The performance of the two methods is demonstrated on numerical examples. The results show that method 2 provides good solutions fast and with little performance degradation comparing with method 1. Then, we apply method 2 to optimize the capacity and to select the combination of the storage devices, and demonstrate the performance by numerical examples.
Bipolar Disorder and Quality of Life: A Patient-Centered Perspective

Several quantitative studies have now examined the relationship between quality of life (QoL) and bipolar disorder (BD) and have generally indicated that QoL is markedly impaired in patients with BD. However, little qualitative research has been conducted to better describe patients’ own experiences of how BD impacts upon life quality. We report here on a series of in-depth qualitative interviews we conducted as part of the item generation phase for a disease-specific scale to assess QoL in BD.  We conducted 52 interviews with people with BD (n=35), their caregivers (n=5) and healthcare professionals (n=12) identified by both convenience and purposive sampling. Clinical characteristics of the affected sample ranged widely between individuals who had been clinically stable for several years through to inpatients who were recovering from a severe episode of depression or mania. Interviews were tape recorded, transcribed verbatim and analyzed thematically.  Although several interwoven themes emerged from the data, we chose to focus on 6 for the purposes of this paper: routine, independence, stigma and disclosure, identity, social support and spirituality. When asked to prioritize the areas they thought were most important in determining QoL, the majority of participants ranked social support as most important, followed by mental health.  Findings indicate that there is a complex, multifaceted relationship between BD and QoL. Most of the affected individuals we interviewed reported that BD had a profoundly negative effect upon their life quality, particularly in the areas of education, vocation, financial functioning, and social and intimate relationships. However, some people also reported that having BD opened up new doors of opportunity.
Internet of Things based garbage monitoring system

In today's busy world time is a vital issue which can't be managed by noticing each and every phenomenon with our tight schedule. So now a day's Automatic systems are being preferred over manual system to make life simpler and easier in all aspects. To make it a grand success Internet of Things is the latest internet technology developed. The number of users of internet has grown so rapidly that it has become a necessary part of our daily life. Our matter of concern in this project is development of Internet of Things based Garbage Monitoring System. As the population of world is increasing day by day, the environment should be clean and hygienic for our better life leads. In most of the cities the overflowed garbage bins are creating an obnoxious smell and making an unhygienic environment. And this is leading to the rapid growth of bacteria and viruses which are causing different types of diseases. To overcome these situations efficient garbage collection systems are getting developed based on IoT. Various designs have already been proposed and have advantages as well as disadvantages. This paper is a review of Garbage Monitoring System based on IoT.
An approach combined Response Surface Method and Particle Swarm Optimization to ship multidisciplinary design and optimization

Ship design is a complex endeavor requiring the successful coordination of many different disciplines. According to various disciplines requirements, how to get a balanced performance is imperative in ship design. Thus, a all-in-one Multidisciplinary Design Optimization (MDO) approach is proposed to get the optimum performance of the ship considering three disciplines, structure; cargo loads and power of propulsion. In this research a Latin Hypercube Sampling (LHS) is employed to explore the design space and to sample data for covering the design space. For the purpose of reducing the calculation and saving the develop time, a quadratic Response Surface Method (RSM) is adopted as an approximation model for solving the system design problems. Particle Swarm Optimization (PSO) is introduced to search the appropriate design result in MDO in ship design. Finally, the validity of the proposed approach is proven by a case study of a bulk carrier.
1 The Magic of Complex Numbers

The notion of complex number is intimately related to the Fundamental Theorem of Algebra and is therefore at the very foundation of mathematical analysis. The development of complex algebra, however, has been far from straightforward.1 The human idea of ‘number’ has evolved together with human society. The natural numbers (1, 2, . . . ∈ N) are straightforward to accept, and they have been used for counting in many cultures, irrespective of the actual base of the number system used. At a later stage, for sharing, people introduced fractions in order to answer a simple problem such as ‘if we catch U fish, I will have two parts 5 U and you will have three parts 3 5 U of the whole catch’. The acceptance of negative numbers and zero has been motivated by the emergence of economy, for dealing with profit and loss. It is rather impressive that ancient civilisations were aware of the need for irrational numbers such as √ 2 in the case of the Babylonians [77] and π in the case of the ancient Greeks.2 The concept of a new ‘number’ often came from the need to solve a specific practical problem. For instance, in the above example of sharing U number of fish caught, we need to solve for 2U = 5 and hence to introduce fractions, whereas to solve x2 = 2 (diagonal of a square) irrational numbers needed to be introduced. Complex numbers came from the necessity to solve equations such as x2 = −1.
Cybersecurity in healthcare: A systematic review of modern threats and trends.

The adoption of healthcare technology is arduous, and it requires planning and implementation time. Healthcare organizations are vulnerable to modern trends and threats because it has not kept up with threats.



The objective of this systematic review is to identify cybersecurity trends, including ransomware, and identify possible solutions by querying academic literature.



The reviewers conducted three separate searches through the CINAHL and PubMed (MEDLINE) and the Nursing and Allied Health Source via ProQuest databases. Using key words with Boolean operators, database filters, and hand screening, we identified 31 articles that met the objective of the review.



The analysis of 31 articles showed the healthcare industry lags behind in security. Like other industries, healthcare should clearly define cybersecurity duties, establish clear procedures for upgrading software and handling a data breach, use VLANs and deauthentication and cloud-based computing, and to train their users not to open suspicious code.



The healthcare industry is a prime target for medical information theft as it lags behind other leading industries in securing vital data. It is imperative that time and funding is invested in maintaining and ensuring the protection of healthcare technology and the confidentially of patient information from unauthorized access.
IEEE 1451-1-6: Providing common network services over MQTT

1451 has been around for almost 20 years and in that time it has seen many changes in the world of smart sensors. One of the most distinct paradigms to arise was the Internet-of-Things and with it, the popularity of light-weight and simple to implement communication protocols. One of these protocols in particular, MQ Telemetry Transport has become synonymous with large cloud service providers such as Amazon Web Services, IBM Watson, and Microsoft Azure, along with countless other services. While MQTT had be traditionally used in controlled networks within server centers, the simplicity of the protocol has caused it to be utilized on the open internet. Now being called the language of the IoT, it seems obvious that any standard that is aiming to bring a common network service layer to the IoT architecture should be able to utilize MQTT. This paper proposes potential methodologies to extend the Common Architectures and Network services found in the IEEE 1451 Family of Standard into applications which utilize MQTT.
A review of opinion mining and sentiment classification framework in social networks

The Web has dramatically changed the way we express opinions on certain products that we have purchased and used, or for services that we have received in the various industries. Opinions and reviews can be easily posted on the Web, such as in merchant sites, review portals, blogs, Internet forums, and much more. These data are commonly referred to as user-generated content or user-generated media. Both the product manufacturers, as well as potential customers are very interested in this online ‘word-of-mouth’, as it provides product manufacturers information on their customers likes and dislikes, as well as the positive and negative comments on their products whenever available, giving them better knowledge of their products limitations and advantages over competitors; and also providing potential customers with useful and ‘first-hand’ information on the products and/or services to aid in their purchase decision making process. This paper discusses the existing works on opinion mining and sentiment classification of customer feedback and reviews online, and evaluates the different techniques used for the process. It focuses on the areas covered by the evaluated papers, points out the areas that are well covered by many researchers and areas that are neglected in opinion mining and sentiment classification which are open for future research opportunity.
Emerging optical access network technologies for 5G wireless [invited]

With the advancement of radio access networks, more and more mobile data content needs to be transported by optical networks. Mobile fronthaul is an important network segment that connects centralized baseband units (BBUs) with remote radio units in cloud radio access networks (C-RANs). It enables advanced wireless technologies such as coordinated multipoint and massive multiple-input multiple-output. Mobile backhaul, on the other hand, connects BBUs with core networks to transport the baseband data streams to their respective destinations. Optical access networks are well positioned to meet the first optical communication demands of C-RANs. To better address the stringent requirements of future generations of wireless networks, such as the fifth-generation (5G) wireless, optical access networks need to be improved and enhanced. In this paper, we review emerging optical access network technologies that aim to support 5G wireless with high capacity, low latency, and low cost and power per bit. Advances in high-capacity passive optical networks (PONs), such as 100 Gbit/s PON, will be reviewed. Among the topics discussed are advanced modulation and detection techniques, digital signal processing tailored for optical access networks, and efficient mobile fronthaul techniques. We also discuss the need for coordination between RAN and PON to simplify the overall network, reduce the network latency, and improve the network cost efficiency and power efficiency.