Miracle-dz/UniFAR-FTUs huggingface dataset:
Design of Light-tree Based Optical Datacenter Networks

Nowadays, people’s daily life is increasingly dependent on Internet applications provided by cloud service providers (CSP), that replicate their content among geographically distributed datacenters using inter-datacenter wide area networks to meet performance and reliability requirements. This paper provides means for efficient design of datacenter networks with static traffic scenarios, where unicast and multicast connection requests are known a priori along with their start and end times. Also, the optical channel setup time is given. Integer Linear Programming (ILP) formulations that consider light-tree and lightpath connections are developed to minimize the network resource consumption. Since solving the ILP formulations is timeconsuming for large networks, we also propose efficient heuristic algorithms. We demonstrate by simulations an advantage in efficiency of a light-tree based heuristic algorithm over its lightpath counterpart. This is due to its ability to construct and extend light-trees to groom more connections. Both heuristic algorithms perform very close to the corresponding ILP optimal result in a case of a small network.
GUIDANCE FOR A FAILING SYSTEM

In each issue of Health Progress in 1995, the journal's 75th anniversary logo highlights an article of particular significance to the Catholic health ministry. T he numerous changes affecting the healthcare ministry raise questions about the organization and delivery of its services; the communa l aspects of these services; the financing of services across the delivery spectrum; the nature and structure of professional-patient relationships; and the ethical principles that have traditionally been used to address conflicts between these various goods. Healthcare analysts and consu l t an t s say these changes represent a paradigm shift. EthicistS and others concerned with the ethical aspects of these changes ask whether they can be adequately addressed through "principleism"—that is, reliance on the four major ethical principles nonmaleficence, beneficence, autonomy, and justice.
ANALYSIS OF FACTORS INHIBITING AVIATION CARGO LOGISTICS IN NIGERIA

This study examined the factors inhibiting aviation cargo logistics in Nigeria. The study adopted multi-stage sampling technique. Air cargo service companies were purposely selected. Eight (8) quoted air cargo companies were stratified and air freight forwarders of each company were equally randomly selected. Three hundred (450) questionnaires were distributed to the respondents and 445 were retrieved. Relative Importance Index (RII) was used to identify the major factors inhibiting aviation cargo logistics in Nigeria. The result showed that increasing fuel price (RII = 0.944), custom bottlenecks (R.I.I = 0.908), high cost of ground handling (R.I.I. = 0.906) and security treats (R.I.I = 0.842) are the most identified factors inhibiting aviation cargo logistics. Furthermore, the result showed that weather conditions and uncertainties at airports were ranked equally hence (R.I.I = 0.640) while changing inventory strategies and mode shifting have the least ranking with (R.I.I = 0.548) and (R.I.I = 0.517) respectively. Conclusively, the study recommended that since increasing fuel price, custom bottlenecks, high cost of ground handling and security treats are found to inhibitaviation cargo logistics, relevant stakeholders and Federal Government of Nigeria should design trade off to accommodate these factors.
PR EP RI NT Runtime Analysis of Whole-System Provenance

Identifying the root cause and impact of a system intrusion remains a foundational challenge in computer security. Digital provenance provides a detailed history of the flow of information within a computing system, connecting suspicious events to their root causes. Although existing provenance-based auditing techniques provide value in forensic analysis, they assume that such analysis takes place only retrospectively. Such post-hoc analysis is insufficient for realtime security applications; moreover, even for forensic tasks, prior provenance collection systems exhibited poor performance and scalability, jeopardizing the timeliness of query responses. We present CamQuery, which provides inline, realtime provenance analysis, making it suitable for implementing security applications. CamQuery is a Linux Security Module that offers support for both userspace and in-kernel execution of analysis applications. We demonstrate the applicability of CamQuery to a variety of runtime security applications including data loss prevention, intrusion detection, and regulatory compliance. In evaluation, we demonstrate that CamQuery reduces the latency of realtime query mechanisms, while imposing minimal overheads on system execution. CamQuery thus enables the further deployment of provenance-based technologies to address central challenges in computer security. Preprint: the final version of this paper will appear in the proceedings of the 25th ACM Conference on Computer and Communications Security in October 2018 (https://www.sigsac.org/ccs/ CCS2018/).
Featherweight-Trait Java : A Trait-based Extension for FJ

In the context of statically typed class-based languages, we investigate classes which might extend upon trait composition. Building classes by composing method-clusters is a well-known technique in implementing object- and class-based languages with simple inheritance, that has been explored in an untyped setting as a first-class mechanism available to the user only recently. This paper presents Featherweight-Trait Java (FTJ), a conservative extension of Featherweight Java (FJ), a simple light-weight class-based calculus take off with statically typed traits. In FTJ, classes can be built using traits as a basic behavioral brick; every trait contains only behavior and no state. Method conflicts between traits must be resolved explicitly by the user either (1) by aliasing or excluding method names, or (2) overriding explicitly in the class. A special emphasis has been put on dealing with "diamond'' conflict, a classical issue playing with multiple inheritance. That makes a kind of multiple inheritance not only possible but simple. As such, FTJ is as a proper extension of FJ. We present a new operational semantics with a new dynamic lookup algorithm, and a new sound type system that guarantees that evaluating a well-typed expression never yields a "message not understood'' run-time error nor get the interpreter stuck. We give an example which illustrates the increased expressive power of the typed trait-based (multiple inheritance) model of FTJ with respect to the classical (single inheritance) typed class-based one of FJ. The resulting calculus appears to be a good starting point for a rigorous mathematical analysis of typed trait-based languages, and a novel paradigm for typed trait-oriented programming.
Comparison of EEG Devices for Eye State Classification

In this paper, we investigate whether the price of an EEG device is directly correlated with the quality of the obtained data when applied to a simple classification task. The data of three different devices (one medical and two consumer) was used to determine the eye state (open or closed). For classification, 83 machine learning algorithms were used on the raw EEG data. While the cheapest device performed extremly poor with only one classifier better than the majority vote the other two devices achieved high accuracy. The lowest error rate for a more expensive consumer EEG was 1.38% and produced by KStar. For the medical device the best performing classifier was IBk which achieved an error rate of 1.63%. Except for KStar, the classifiers achieved a lower error rate by the medical EEG measurement system than the consumer EEG system.
ENERGY SAVING SCHEME OF OPTIMIZED BY GREEN COMMUNICATION TECHNOLOGY BASED ON MULTICARRIER BASE STATIONS USING OFDMA

As mobile knowledge traffic levels have hyperbolic exponentially, leading to rising energy prices in recent years, the demand for and development of inexperienced communication technologies has resulted in numerous energy-saving styles for cellular systems. At identical time, recent technological advances have allowed multiple part carriers (CCs) to be at the same time utilized in a very base station (BS), a development that has created the energy consumption of BSs a matter of accelerating concern. Digital signal process came great distance from wirebased glass fiber communication to wireless-based high rate supported communication models. Radio waves supported long distance satellites, radars to microwave supported mobiles has modified in terms of technology and rate in last twenty years. Mobile communication has become a part of everyday life and mobile usage has witness huge growth leads to high energy consumption that remains involved space in resource management. inexperienced communication technology is planned during this paper for effectively dominant the date rate and power consumption to avoid wasting the energy. the matter of energy diminution at baccalaureate transceivers subject to sure quality-of-service and fairness needs for all users is self-addressed during this work supported communication activities in downlink transmissions of the baccalaureate with orthogonal frequency-division multiple access-based multi CCs square measure thought-about. Experimental results reveal that planned methodology yields higher results than ancient algorithms. By treatment SUI channel model that take into account Height of antenna, piece of ground kind, Doppler unfold, LOS conditions square measure fastened. Additionally cell size, BTS antenna height, receiver antenna height, BTS antenna beam width, receiver antenna beam width, vertical polarizations square measure thought-about to urge honest system providing as per required data rate.
Observation of chaotic ELMs in HL-2A tokamak

The high confinement mode (H-mode) operation is recently obtained in HL-2A divertor configuration, the corresponding edge localized mode (ELM) is recognized as being of type III. Time intervals in ELM time series are analysed to obtain the information about the ELM process. Signatures of unstable periodic orbits (UPOs) are detected, which are indicators of chaos and may be used to control the big ELM events.
The Applications of Machine Learning Techniques in Networking Area Exam

The growing complexity and scale of Internet systems coupled with the improved capabilities of Machine Learning (ML) methods in recent years have motivated researchers and practitioners to increasingly rely on these methods for datadriven design and analysis of wide range of problems in network systems such as detecting network attacks, performing resource management, or improving quality of service (QoS). In this survey, we review a large number of prominent research papers that apply ML methods to design, analysis or evaluation of network systems. To this end, we divide these studies into the following six groups based on the area of network systems that they target: 1) Domain name system, 2) Application identification, 3) QoS, 4) Cloud services, 5) Network security, and 6) Traffic prediction. Within each group, we examine the type of ML methods as well as input datasets that are used by individual studies, describe how they address various challenges, and summarize their key findings. In particular, we explore how domain knowledge in networking can inform different aspects of applying ML techniques such as problem formulation, feature engineering, feature selection, and deployment. We summarize representative common practices in the networking community along with a number of remaining challenges and research gaps.
20 The Study on Secure RFID Authentication and Access Control

In recent years, Radio Frequency Identification (RFID) technology is rapid progress and has been widely used in daily life. RFID systems consist of three components: radio frequency (RF) tags, RF readers and a back-end database server. A passive RFID tag is a microchip capable of transmitting a static identifier or serial number for a short distance. Readers query tags for their contents by broadcasting an RF signal. Tags respond with resident data, such as a unique serial number. Tag data may be read automatically without line of sight. RFID systems have many applications in supply chain managements, inventory control, anti-counterfeiting, ticketing systems, healthcare and smart home developments. However, it may bring up some privacy threats. Anyone can easily access tagged items and collect data without line of sight that personal privacy under threat. The most concerned issues are the tracking and the location privacy. Based on the characteristic of outstanding traceability, the history of the tag’s location might be identified as a tag’s information is intercepted and collected by the attacker in different location. For instance, the unique tag’s EPC data can be used to trace a person or an object carrying a tag in time and space. The collected information can be merged and linked in order to generate a person’s profile. It will be a serious problem as RFID tags are widely used. Without privacy protection, a person with carried RFID tags can be tracked and profiled by unauthorized people. The unique information of the items may be indicated that a customer carrying those tags is subject to track from unauthorized readers. Ideal RFID systems used in product lifecycle should satisfy high confidentiality, anonymity, integrity and high availability (Gao et al., 2004; Pisarsky, 2004). The product life cycle is a procedure that the product from manufacture to be recycled. This procedure from the perspective of commerce can be divided into five stages(Figure 1): (1)&(2) are the stage of “production to retail store” (business-to-business) , (3) is the stage of “retail store to customer” (business-to-customer), (4) is the stage of “individual sales” (customer-tocustomer), (5)&(6) are the stage of “after-sales service”, and (7) is the stage of “recycling” (reverse logistics). Since a tag is embedded in the product, security risks such as privacy threats may be occurred in each stage of the product life cycle.
A real time mobile-based face recognition with fisherface methods

Face Recognition is a field research in Computer Vision that study about learning face and determine the identity of the face from a picture sent to the system. By utilizing this face recognition technology, learning process about people’s identity between students in a university will become simpler. With this technology, student won’t need to browse student directory in university’s server site and look for the person with certain face trait. To obtain this goal, face recognition application use image processing methods consist of two phase, pre-processing phase and recognition phase. In pre-processing phase, system will process input image into the best image for recognition phase. Purpose of this pre-processing phase is to reduce noise and increase signal in image. Next, to recognize face phase, we use Fisherface Methods. This methods is chosen because of its advantage that would help system of its limited data. Therefore from experiment the accuracy of face recognition using fisherface is 90%.
Mining of Fuzzy Association Rules using a Kernel-based Self-Organized Map for partitioning large databases

The extraction of fuzzy association rules for the description of dependencies and interactions from large data sets as those arising in gene expression data analysis applications perplexes very difficult combinatorial problems that depend heavily on the size of these sets. The paper describes a two stage approach to the problem that obtains computat ionally manageable solutions. The first stage aims to cluster transactions that more probably are associated. Thereafter, the second stage, the fuzzy association rule extraction follows, confronting a significantly reduced problem. The clustering phase is accomplished by means of a Kernel Supervised Dynamic Grid SelfOrganized Map (KSDGSOM) utilizing the mutual informa tion metric. This metric allows the formation of data clusters that maximize the mutual informa tion for transactions of the same cluster and to minimize it between different clusters. Subsequently, the fuzzy association rules are extracted locally on a per cluster basis . The paper applies the techniques for mining gene expression data. KeyWords : Fuzzy Association Rules, Mutual Information, Clustering, SelfOrganized Maps, Entropy, Genome Data Mining, Gene Expression Analysis
Cape Town with Interactive Computational Synthesis Methods

Although Cape Town city in South Africa is generally regarded as the most stable and prosperous city in the region, there are still approximately 7.5 million people living in informal settlements and about 2.5 million housing units are needed (reference to website excluded for review). This motivates the so-called Empower Shack project, aiming to develop upgrading strategies for these informal settlements. To facilitate the fulfilment of this project, urban design prototyping tools are researched and developed with the capabilities for fast urban design synthesis. Therefore, with this paper we present a computational method for fast interactive synthesis of urban planning prototypes. For the generation of mock-up urban layouts, one hierarchical slicing structure, namely, the slicing tree is introduced as an abstract representation of the parcels as an extension of the existing generative method for street network. It has been proved that our methods can interactively assist the urban planning process in practice. However, the newly introduced data structure has several limitations and hinders the further improvement of urban synthesis. In the future, the development of a new data structure is required to fulfil the optimization methods for urban synthesis and evaluation strategies should be enabled to fully realize the computational support.
Ultrasound imaging system with pixel oriented processing

An ultrasound imaging system with pixel oriented processing is provided in which an acoustic signal is generated, echoes from the acoustic signal are received at a plurality of receiving elements to obtain echo signals that are then stored, a given pixel is mapped into a region of the stored signals, the mapped region of the stored echo signals is organized into array for the given pixel after which the array is processed to generate a signal response for the given pixel to obtain acoustic information for the given pixel. The system can be implemented entirely on plug-in cards for a commercial PC motherboard. The system and method can be implemented for pixel-oriented or voxel-oriented image processing and display, eliminating intermediate data computations and enabling extensive use of software processing methods. Advantages include improved acquisition of signal dynamic range, flexible acquisition modes for high frame rate 2D, 3D, and Doppler blood flow imaging.
1 A tRNA modification balances carbon and nitrogen metabolism by regulating phosphate 1 homeostasis

10 Cells must appropriately sense and integrate multiple metabolic resources to commit to 11 proliferation. Here, we report that S. cerevisiae cells regulate carbon and nitrogen metabolic 12 homeostasis through tRNA U34-thiolation. Despite amino acid sufficiency, tRNA-thiolation deficient 13 cells appear amino acid starved. In these cells, carbon flux towards nucleotide synthesis decreases, 14 and trehalose synthesis increases, resulting in a starvation-like metabolic signature. Thiolation 15 mutants have only minor translation defects. However, in these cells phosphate homeostasis genes 16 are strongly down-regulated, resulting in an effectively phosphate-limited state. Reduced phosphate 17 enforces a metabolic switch, where glucose-6-phosphate is routed towards storage carbohydrates. 18 Notably, trehalose synthesis, which releases phosphate and thereby restores phosphate availability, 19 is central to this metabolic rewiring. Thus, cells use thiolated tRNAs to perceive amino acid 20 sufficiency, balance carbon and amino acid metabolic flux and grow optimally, by controlling 21 phosphate availability. These results further biochemically explain how phosphate availability 22 determines a switch to a ‘starvation-state’. 23
Swarm-Intelligence-Based Communication Protocols for Wireless Sensor Networks

Social insect communities are formed from simple, autonomous, and cooperative organisms that are interdependent for their survival. These communities are able to effectively coordinate themselves to achieve global objectives despite a lack of centralized planning, and the behaviour is referred to as swarm intelligence. This chapter presents a study of communication protocols for wireless sensor networks utilizing nature-inspired systems: social insect-based communities and natural creatures. Three types of insects are used for discussion: ants, termites, and bees. In addition, a study of the social foraging behavior of spider monkeys is presented. The performances of these swarm-intelligence-based algorithms were tested on common routing scenarios. The results were compared with other routing algorithms with varying network density and showed that swarm-intelligence-based routing techniques improved on network energy consumption with a control over best-effort service. The results were strengthened with a model of termite-hill routing algorithm for WSN. Swarm-Intelligence-Based Communication Protocols for Wireless Sensor Networks
National Forests in the Sierra Nevada: A Conservation Strategy

Special interest areas (SIA) are authorized under CFR 36 294.1 and defined as areas which should be managed principally for recreation use substantially in their natural condition. They are managed for their unique scenic, geologic, historical, archaeological, botanical, cultural, or other memorable features. Research Natural Areas (RNA) are authorized under Forest Service Manual (FSM) Section 4063 and defined as a physical or biological unit in which current natural conditions are maintained insofar as possible. These conditions are ordinarily achieved by allowing natural physical and biological processes to prevail without human intervention to provide a baseline against which man-caused changes elsewhere can be measured (Moir 1972; Burns et al 1984). RNAs are established specifically to preserve a representative example of an ecological community primarily for scientific and educational purposes. The FSM 4063.1 states: "Research Natural Areas must be large enough to provide essentially unmodified conditions within their interiors. In the West, 300 acres of land is generally considered the minimum size. " However, in order to represent a variety of successional stages, landscape patterns, plant associations, and environmental variables, RNAs for some ecosystem types will often need to be considerably larger than 300 acres. Some proposed RNAs in the Rocky Mountain Region currently exceed 5,000 acres. The viability of species and persistence of natural disturbance patterns are also often size dependent (Andrews 1993).
2 Carrier sense in Ethernet

Last lecture, we looked at the ALOHA protocol for medium access control (MAC). The ALOHA protocol pioneered two main ideas: the ability to detect and handle collisions on a shared medium and the use of randomization to decide whether to transmit a packet or not. However, ALOHA was designed for situations where none of the users could hear any of the other users transmitting. Real-world wireless deployments are not always this bad, and oftentimes users do have the ability to hear each other’s transmissions—an ability called carrier sense. This lecture, we’ll look at a few examples of how to incorporate carrier sense into the MAC protocol.