Miracle-dz/UniFAR-FTUs huggingface dataset:
CA Computer Architecture

This electronic book is copyrighted, and protected by the copyright laws of the United States. This (and all associated documents in the system) must contain the above copyright notice. If this electronic book is used anywhere other than the project's original system, CSEP must be notiied in writing (email is acceptable) and the copyright notice must remain intact. 1 Overview The advantages of programming in a high level language include abstraction and portability. Abstraction means programmers can describe algorithms in a \high level" notation that is independent of details about the machine that will execute the algorithm. Portability is a byproduct of abstraction that allows programs to be run on a wide variety of computers as long as there is a compiler that will translate them for each machine. In most programming situations reality is close to the ideal. Compilers for many high level languages are very good at generating eecient and portable code for typical computer systems, so programmers are able to express algorithms in high level languages and expect them to run eeciently on almost any machine. There may be a few isolated places where a programmer who invests a lot of eeort may be able to write a more eecient routine in assembly language (the native language of the machine), but it is hardly ever worth the eeort to write an entire program in assembly language. Obviously when all or part of a program is written in assembler it is not as abstract, since assembly language is the language of the machine and not the language of the application, and it is no longer portable from one machine to another. It is not necessary to write a lower level program in order to compromise abstraction and portability. As a simple example, suppose a program multiplies a value x by 2. The obvious way to write this in C is \2*x". But if a programmer knows the machine that will execute this program has a slow multiplication instruction, and knows that integers are represented in binary, she can use the expression \x << 1" instead. 1 The resulting program is less abstract 1 In C \2*x" means \shift x left one bit", an operation that most machines do very eeciently. The binary number system and why shifting left is equivalent to multiplication will be described later in this chapter, and the C programming language is described in the …
Supporting treatment of people living with HIV / AIDS in resource limited settings with IVRs

We developed an interactive voice response (IVR) system called TAMA (Treatment Advice by Mobile Alerts) that provides treatment support to people living with HIV / AIDS (PLHA) in developing countries, who are on antiret-roviral therapy (ART). We deployed TAMA with 54 PLHA in 5 HIV clinics in India for a period of 12 weeks. During the study, we gathered feedback about TAMA's design and usage. Additionally, we conducted detailed qualitative interviews and analysed usage logs. We found that TAMA was usable and viable in the real life settings of PLHA and it had many desirable effects on their treatment adherence. We developed insights that inform the design of TAMA and some of these can be generalised to design of other long-term, frequent-use IVR applications for users in developing countries in the healthcare domain and beyond.
Optimization of green agri-food supply chain network using chaotic PSO algorithm

In this paper, a chaotic Particle Swarm Optimization (CPSO) algorithm is presented to solve the green agri-food supply chain network (GASCN). The GASCN design is critical to reduce the total transportation cost for efficient and effective supply chain management. The traditional supply chain does not adequately satisfy the expectance of all the customers, therefore new model of supply chain of great urgency to be exploited. The main contribution of this paper is to find an optimal solution for GASCN problem and propose a new solution based on CPSO to optimize the GASCN. To show the efficacy of the CPSO algorithm, the algorithm is tested on three cases. Results show better performance of the CPSO in GASCN by both optimization speed and solution quality as compared to GA and CGA, especially when the scale of problem is large.
Improving person detection using synthetic training data

Person detection in complex real-world scenes is a challenging problem. State-of-the-art methods typically use supervised learning relying on significant amounts of training data to achieve good detection results. However, labeling training data is tedious, expensive, and error-prone. This paper presents a novel method to improve detection performance by supplementing real-world data with synthetically generated training data. We consider the case of detecting people in crowded scenes within an AdaBoost-framework employing Haar and Histogram-of-Oriented-Gradients (HOG) features. Our evaluations on real-world video sequences of crowded scenes with significant occlusions show that the combination of real and synthetic training data significantly improves overall detection results.
A Novel Face Encoding Algorithm Based On Local Directional Number Pattern

: Edge response in terms of direction and number will vary from person to person and expression to expression and can be used for face and expression recognition. Encoding these face features in a compact form is a must to obtain the discriminant information. This is a hot research topic and many works have already been done on the same. This paper proposes a novel algorithm based on Local Directional Number Pattern (LDN) for encoding edge responses and directional information of an image in an effective manner. Choice of appropriate edge detection method is very important for finding the absolute gradient magnitude for edges. Kirsch Compass Mask (KCM), a popular edge detection operator which uses the derivative approximation to find edges is used in this work. This paper also discusses two variants of edge detection namely Slow KCM (SKCM) approach which is computationally more complex and Fast KCM (FKCM) approach which is less complex. Analysis of edge responses in different expressions namely normal, smile, surprise, disgust, and sad, using the proposed algorithm is presented in this paper. The results show that LDN coded image can be used as unique feature descriptor in face and expression recognition.
Lyn Is Essential for Fcγ Receptor III–Mediated Systemic Anaphylaxis but Not for the Arthus Reaction

The Src family kinase Lyn initiates intracellular signal transduction by associating with a variety of immune receptors such as antigen receptor on B cells and high-affinity Fc receptor (FcR) for immunoglobulin Ig(E) (FcεRI) on mast cells. Involvement of Lyn in the IgE-mediated immediate-type hypersensitivity is well documented, but the physiological significance of Lyn in IgG-dependent, type III low-affinity FcR for IgG (FcγRIII)-mediated responses is largely unknown. In this study, we generated a double-mutant mouse strain deficient in both type II FcR for IgG (FcγRIIB) and Lyn to exclude any involvement of inhibitory signaling by FcγRIIB, which otherwise downregulates FcγRIII-mediated cellular responses. FcγRIIB-deficient but Lyn-sufficient mice served as controls. The Lyn deficiency attenuated IgG-mediated systemic anaphylaxis in vivo, and significantly reduced calcium mobilization and degranulation responses of bone marrow–derived mast cells (BMMCs) in vitro. However, we found that either interleukin 4 or tumor necrosis factor α release by BMMCs was comparable to that from Lyn-deficient and control mice, and the reverse-passive Arthus reaction was equally induced in both mutant mice, indicating that Lyn is not involved in the onset of the IgG-mediated, FcγRIII-dependent late phase responses of mast cells. These findings provide us with insight into distinct signaling mechanisms in mast cells underlying the development of diverse pathologies as well as a therapeutic potential for selective treatment of allergic disorders.
Optimized pathological and visual content-based neuroimaging retrieval

Neuroimaging provides important insights for understanding neurobiology and is essential for accurate neurological and neurosurgical diagnosis and patient care. The volume and complexity of the neuroimaging datasets have greatly increased due to advances in scanning instrumentation. These large datasets now pose challenges for images retrieval / management and more effective approaches are needed. Content-based image retrieval (CBIR) takes advantage of the rich visual/physiological information in the images and can provide the opportunity for more efficient and reliable image retrieval. Although a number of investigators have used CBIR systems in neuroimaging, few of these approaches have explored all the potential features in these images. We suggest that such image retrieval could be optimized by using pathological and domain-specific visual features rather than texture features alone. We used the cerebral metabolic rate of glucose (CMRGlc) as the physiological parameter from static brain [ F ] 2-fluorodeoxy-glucose (FDG) positron emission tomography (PET) images and a customized disorder-oriented mask (DOM) specific for a particular neurodegenerative disorder, with the regions of interest (ROIs) specific for each disease sub-type. We designed 8 Gabor filter banks with different parameter settings and identified the optimum Gabor function parameter setting for the visual feature extraction. Our experimental data indicate that optimization of the Gabor filter parameters, targeted to disease specific regions enhances retrieval precision.
QoI-Based Data Upload Control for Mobility-Aware Cloud Services

Mobility-aware cloud services such as fleet management systems need to understand the positions of mobile devices accurately in a real-time manner. Generally speaking, positioning accuracy and data traffic load are in a trade-off relation. Highly accurate real-time positioning requires frequent location data upload and hence results in heavy data traffic load. Although not all data are equally important, data of low importance often consumes a lot of network resources. This paper presents a data upload control method that the dynamically assesses quality of information (QoI) of measured data at mobile devices. The proposed method balances high accuracy with low traffic loads to achieve efficient vehicle position management. We evaluated the performance of the proposed method using both artificial and actual GPS data and confirmed that it successfully controlled the accuracy and network traffic load according to application requirements.
Energy optimal pulse pattern for Z-source inverter to increase the efficiency of electric drive systems in automotive applications

In automotive applications, the Z-source inverter is a single stage inverter that provides the useful feature of boosting the DC-link voltage to a desired value independently of the battery voltage. The advantage of an adjustable DC-link voltage can be used as a degree of freedom for a loss minimized control of electric drives. However, the semiconductors experience high stress during boost operation. This paper presents pulse patterns that reduce power electronic losses during boost operation.
ePub WU Institutional Repository Thomas Baier and

While the maturity of process mining algorithms increases and more process mining tools enter the market, process mining projects still face the problem of different levels of abstraction when comparing events with modeled business activities. Current approaches for event log abstraction try to abstract from the events in an automated way that does not capture the required domain knowledge to fit business activities. This can lead to misinterpretation of discovered process models. We developed an approach that aims to abstract an event log to the same abstraction level that is needed by the business. We use domain knowledge extracted from existing process documentation to semi-automatically match events and activities. Our abstraction approach is able to deal with n:m relations between events and activities and also supports concurrency. We evaluated our approach in two case studies with a German IT outsourcing company.
On demand dependent deactivation of automotive ECUs

We describe details of a technology under development that allows selective deactivation of electronic control units in automotive networks as a means to increase a vehicle's energy efficiency: intelligent communication controllers. In particular, we provide details on an ICC's estimated energy savings potential, prove by experiment that ICCs are unique enablers for deactivation of FlexRay ECUs, and describe a prototypical implementation.
Evaluation of Femoral Tunnel Positioning Using 3-Dimensional Computed Tomography and Radiographs after Single Bundle Anterior Cruciate Ligament Reconstruction with Modified Transtibial Technique

Background The purpose of this study is to report a modified transtibial technique to approach the center of anatomical femoral footprint in anterior cruciate ligament (ACL) reconstruction and to investigate the accurate femoral tunnel position with 3-dimensional computed tomography (3D-CT) and radiography after reconstruction. Methods From December 2010 to October 2011, we evaluated 98 patients who underwent primary ACL reconstruction using a modified transtibial technique to approach the center of anatomical femoral footprint in single bundle ACL reconstruction with hamstring autograft. Their femoral tunnel positions were investigated with 3D-CT and radiography postoperatively. Femoral tunnel angle was measured on the postoperative anteroposterior (AP) radiograph and the center of the femoral tunnel aperture on the lateral femoral condyle was assessed with 3D-CT according to the quadrant method by two orthopedic surgeons. Results According to the quadrant method with 3D-CT, the femoral tunnel was measured at a mean of 32.94% ± 5.16% from the proximal condylar surface (parallel to the Blumensaat line) and 41.89% ± 5.58% from the notch roof (perpendicular to the Blumensaat line) with good interobserver (intraclass correlation coefficients [ICC], 0.766 and 0.793, respectively) and intraobserver reliability (ICC, 0.875 and 0.893, respectively). According to the radiographic measurement on the AP view, the femoral tunnel angles averaged 50.43° ± 7.04° (ICC, 0.783 and 0.911, respectively). Conclusions Our modified transtibial technique is anticipated to provide more anatomical placement of the femoral tunnel during ACL reconstruction than the former traditional transtibial techniques.
Depth Camera Image Preprocessing and 3 D Projection Depth Data Point Cloud Digital Model Point Cloud Surface Normal Estimation Registration

The ability to directly acquire 3D scene information from a single viewpoint could have a large impact on many computer vision applications. Depth cameras are a new sensing device facilitating such data acquisition, but are limitated by occlusion, noise, and poor sampling of obliquely viewed surfaces. To extend the applicability of a single depth camera, we propose a method of retaining knowledge of surfaces from depth camera images acquired over time. This method draws on techniques from computer vision and computer graphics to reconstruct a 3D point cloud from a depth image, smooth and consolidate the point cloud into a good model, estimate surface normals of the model points, and register each new depth image to the model for tracking and model update.
A comparison of Si CMOS, SiGe BiCMOS, and InP HBT technologies for high-speed and millimeter-wave ICs

The paper presents an overview of Si MOSFET, SiGe HBT, and InP HBT device and circuit performance for broadband and tuned millimeter-wave applications. Implementations of CMOS-only, SiGe-HBT-only, SiGe BiCMOS, and InP-HBT 30-80 Gb/s high-speed circuit in production 130-nm SiGe BiCMOS and InP HBT technologies are compared.
An F1 Genetic Screen for Maternal-Effect Mutations Affecting Embryonic Pattern Formation in Drosophila melanogaster

Large-scale screens for female-sterile mutations have revealed genes required maternally for establishment of the body axes in the Drosophila embryo. Although it is likely that the majority of components involved in axis formation have been identified by this approach, certain genes have escaped detection. This may be due to (1) incomplete saturation of the screens for female-sterile mutations and (2) genes with essential functions in zygotic development that mutate to lethality, precluding their identification as female-sterile mutations. To overcome these limitations, we performed a genetic mosaic screen aimed at identifying new maternal genes required for early embryonic patterning, including zygotically required ones. Using the Flp-FRT technique and a visible germline clone marker, we developed a system that allows efficient screening for maternal-effect phenotypes after only one generation of breeding, rather than after the three generations required for classic female-sterile screens. We identified 232 mutants showing various defects in embryonic pattern or morphogenesis. The mutants were ordered into 10 different phenotypic classes. A total of 174 mutants were assigned to 86 complementation groups with two alleles on average. Mutations in 45 complementation groups represent most previously known maternal genes, while 41 complementation groups represent new loci, including several involved in dorsoventral, anterior-posterior, and terminal patterning.
A Blind Dynamic Fingerprinting Technique for Sequential Circuit Intellectual Property Protection

Design fingerprinting is a means to trace the illegally redistributed intellectual property (IP) by creating a unique IP instance with a different signature for each user. Existing fingerprinting techniques for hardware IP protection focus on lowering the design effort to create a large number of different IP instances without paying much attention on the ease of fingerprint detection upon IP integration. This paper presents the first dynamic fingerprinting technique on sequential circuit IPs to enable both the owner and legal buyers of an IP embedded in a chip to be readily identified in the field. The proposed fingerprint is an oblivious ownership watermark independently endorsed by each user through a blind signature protocol. Thus, the authorship can also be proved through the detection of different user's fingerprints without the need to separately embed an identical IP owner's signature in all fingerprinted instances. The proposed technique is applicable to both application-specific integrated circuit and field-programmable gate array IPs. Our analyses show that the fingerprint is immune to collusion attack and can withstand all perceivable attacks, with a lower probability of removal than state-of-the-art FSM watermarking schemes. The probability of coincidence of a 32-bit fingerprint is in the order of 10-10 and up to 1035 32-bit fingerprinted instances can be generated for a small design of 100 flip-flops.
A syntactic and functional correspondence between full-reducing normalisers and full-reducing abstract machines

We show how to interderive by means of program transformation steps the semantic artefacts (normalisers and abstract machines) for full-reducing hybrid reduction strategies. A full-reducing strategy reduces terms fully until there is no reducible subterm left. A hybrid strategy relies on a weaker subsidiary strategy. Hybridisation is a necessary condition for a full-reducing strategy to deliver the fully reduced result when it exists. With the current interderivation techniques the abstract machine obtained cannot be refunctionalised. However, the notion of hybridisation suggests a solution. We illustrate the problem and the solution with the interderivation of substitution-based normalisers for normal order, the standard full-reducing strategy of the pure lambda calculus. The machine we obtain is a substitution-based, eval/apply, open-terms version of Pierre Crégut’s full-reducing Krivine machine KN. Thus, we show that it is possible to derive, rather than contrive, full-reducing abstract machines.
Dependency Grammars and Context-Free Grammars

The question arises from time to time what the relation is between dependency grammars (DG’s) and phrase-structure grammars. A classic paper by Gaifman [1] would appear to have laid the issue to rest, by proving that dependency grammars are a special case of context-free grammars (CFG’s). Gaifman proves that dependency grammars are equivalent to a proper subset of phrasestructure grammars, those of degree • 1, which I will dub d1-CFG’s. (As degree cannot be explained in a few words, I will leave it undefined for the moment.) Under a weaker notion of correspondence, which Gaifman attributes to Hays [2], dependency grammars correspond to finite-degree CFG’s, which represent a larger subset of CFG’s, but a proper subset nonetheless. I submit, however, that Gaifman correlates DG’s with a proper subset of CFG’s only by suppressing the essential property of DG’s, namely, their headedness. I would like to show that, if we take headedness seriously, we are led to the conclusion that DG’s and CFG’s both represent equivalence classes of what I will call headed context-free grammars (HCFG’s), but that neither DG’s nor CFG’s subsume the other. Nonetheless, Gaifman’s result is preserved in a different form, in that the equivalence classes defined by CFG’s include all HCFG’s, but the equivalence classes defined by DG’s include only finite-degree HCFG’s. In particular, each HCFG has a unique characteristic grammar, a CFG that abstracts away from the choice of heads in the HCFG. Each HCFG also has a unique projection grammar, a DG representing the dependencies among projections in the headed trees generated by the HCFG. The projection grammar abstracts away from the order in which dependent projections are combined with governing projections. Each relation defines equivalence classes: the class of HCFG’s having the same characteristic grammar, the class of HCFG’s having the same projection grammar. But the equivalence classes are incomparable. There are HCFG’s that have the same characteristic grammar, but different projection grammars; and there are HCFG’s with the same projection grammar, but different characteristic grammars. To flesh out this sketch, we need to define some terms. A DG is a tuple G = (Σ; P; S), where Σ is a set of word categories, P is a set of productions, and S μ Σ is the set of start symbols. Productions are of the form X(fi;fl), where X is a category, and fi; fl are sequences of categories. The productions license dependency trees. A dependency tree is licensed by G iff every node is licensed by some production of G. A production X(Y1; : : : ; Ym;Z1; : : : Zn)
Optimal sampling algorithms for frequency estimation in distributed data

Consider a distributed system with n nodes where each node holds a multiset of items. In this paper, we design sampling algorithms that allow us to estimate the global frequency of any item with a standard deviation of εN, where N denotes the total cardinality of all these multisets. Our algorithms have a communication cost of O(n +√n/ε), which is never worse than the O(n + 1/ε2) cost of uniform sampling, and could be much better when n ≪ 1/ε2. In addition, we prove that one version of our algorithm is instance-optimal in a fairly general sampling framework. We also design algorithms that achieve optimality on the bit level, by combining Bloom filters of various granularities. Finally, we present some simulation results comparing our algorithms with previous techniques. Other than the performance improvement, our algorithms are also much simpler and easily implementable in a large-scale distributed system.